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   <news:title>比較的敵対学習による多様で正確な画像キャプション生成（Generating Diverse and Accurate Visual Captions by Comparative Adversarial Learning）</news:title>
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   <news:title>M31球状星団の恒星X線放射率の測定が示す示唆（A CHANDRA STUDY OF THE STELLAR X-RAY EMISSIVITY OF GLOBULAR CLUSTERS IN M 31 BULGE）</news:title>
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    <news:language>ja</news:language>
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   <news:title>Open Directory Projectベースの大規模分類への単語埋め込みの統合 (Incorporating Word Embeddings into Open Directory Project based Large-scale Classification)</news:title>
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   <news:title>Graphからシーケンスへの学習（GRAPH2SEQ: Graph to Sequence Learning with Attention-based Neural Networks）</news:title>
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   <news:title>階層的マルチラベルマッチャによるパッチベース顔認識 (Patch-based Face Recognition using a Hierarchical Multi-label Matcher)</news:title>
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   <news:title>リソースの少ない言語向け絵文字表現のコントラスト学習（Contrastive Learning of Emoji-based Representations for Resource-Poor Languages）</news:title>
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   <news:title>宇宙大規模構造の分類における深層ニューラルネットワークの適用（Classifying the Large Scale Structure of the Universe with Deep Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>感情は普遍である：リソースが乏しい言語の感情表現を学習する方法（Emotions are Universal: Learning Sentiment Based Representations of Resource-Poor Languages using Siamese Networks）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>進化するネットワークにおけるインフルエンス最大化（Evolving Influence Maximization in Evolving Networks）</news:title>
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   <news:title>コードミックス言語の感情分析手法の実務的意義（Sentiment Analysis of Code-Mixed Languages leveraging Resource Rich Languages）</news:title>
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   <news:title>ランク制約尤度によるマルコフ連鎖の推定（Estimation of Markov Chain via Rank-constrained Likelihood）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>左右比較再帰モデルによるステレオマッチング（Left-Right Comparative Recurrent Model for Stereo Matching）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>非線形凸錐計画に対する確率的プリマル・デュアル座標法（STOCHASTIC PRIMAL-DUAL COORDINATE METHOD FOR NONLINEAR CONVEX CONE PROGRAMS）</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>ニューラル自己回帰フロー（Neural Autoregressive Flows）</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>単一画像からの3次元骨格復元を結ぶ手法の要点（3D Interpreter Networks for Viewer-Centered Wireframe Modeling）</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>コーディング不要の機械学習SaaS: Vanlearningの設計と課題（Vanlearning: A Machine Learning SaaS Application for People Without Programming Backgrounds）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>複数の有向ガウスグラフィカルモデルの高次元共同推定（High-Dimensional Joint Estimation of Multiple Directed Gaussian Graphical Models）</news:title>
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   <news:title>DeepSignsによる深層学習モデルの権利保護（DeepSigns: A Generic Watermarking Framework for Protecting the Ownership of Deep Learning Models）</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>二重群で局所最小を脱出する最適化手法の提案（A Bi-population Particle Swarm Optimizer for Learning Automata based Slow Intelligent System）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-22T16:12:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動微分の本質を掴む――並列化可能で単純な逆モード自動微分の考え方（The Simple Essence of Automatic Differentiation）</news:title>
   <news:publication_date>2026-04-22T16:12:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682256</loc>
  <lastmod>2026-04-22T16:11:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的新規検出による視覚オブジェクト認識の拡張（Hierarchical Novelty Detection for Visual Object Recognition）</news:title>
   <news:publication_date>2026-04-22T16:11:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682254</loc>
  <lastmod>2026-04-22T16:11:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitterのハッシュタグを用いたイベント検出手法（An Event Detection Approach Based On Twitter Hashtags）</news:title>
   <news:publication_date>2026-04-22T16:11:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682252</loc>
  <lastmod>2026-04-22T16:11:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一の視野検査から未来の視野を予測する深層学習（Forecasting Future Humphrey Visual Fields Using Deep Learning）</news:title>
   <news:publication_date>2026-04-22T16:11:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682250</loc>
  <lastmod>2026-04-22T15:20:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電気自動車充電ステーションの利用予測を機械学習で推定する手法（Predicting Electric Vehicle Charging Station Usage）</news:title>
   <news:publication_date>2026-04-22T15:20:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682248</loc>
  <lastmod>2026-04-22T15:19:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>まばらな時空間データのグラフベース深層モデルとリアルタイム予測（Graph-Based Deep Modeling and Real Time Forecasting of Sparse Spatio-Temporal Data）</news:title>
   <news:publication_date>2026-04-22T15:19:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682246</loc>
  <lastmod>2026-04-22T15:19:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトラムセンシングのための敵対的生成学習（Generative Adversarial Learning for Spectrum Sensing）</news:title>
   <news:publication_date>2026-04-22T15:19:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682244</loc>
  <lastmod>2026-04-22T15:18:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユニバーサル・プランニング・ネットワーク（Universal Planning Networks）</news:title>
   <news:publication_date>2026-04-22T15:18:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682242</loc>
  <lastmod>2026-04-22T15:18:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepMVSによる多視点ステレオ復元の学習化（DeepMVS: Learning Multi-view Stereopsis）</news:title>
   <news:publication_date>2026-04-22T15:18:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682240</loc>
  <lastmod>2026-04-22T15:18:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シャッフルされた線形回帰に対する確率的EM（Stochastic EM for Shuffled Linear Regression）</news:title>
   <news:publication_date>2026-04-22T15:18:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682238</loc>
  <lastmod>2026-04-22T15:18:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的教師-生徒学習による教師なしドメイン適応（Adversarial Teacher-Student Learning for Unsupervised Domain Adaptation）</news:title>
   <news:publication_date>2026-04-22T15:18:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682236</loc>
  <lastmod>2026-04-22T14:26:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一量子装置からの量子性の暗号学的検査と証明可能な乱数生成（A Cryptographic Test of Quantumness and Certifiable Randomness from a Single Quantum Device）</news:title>
   <news:publication_date>2026-04-22T14:26:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682234</loc>
  <lastmod>2026-04-22T14:26:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平均-半偏差リスクの再帰的最適化（Recursive Optimization of Convex Risk Measures: Mean-Semideviation Models）</news:title>
   <news:publication_date>2026-04-22T14:26:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682232</loc>
  <lastmod>2026-04-22T14:25:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>耐故障・非部分集合性最大化とマトロイド制約（Resilient Non-Submodular Maximization over Matroid Constraints）</news:title>
   <news:publication_date>2026-04-22T14:25:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682230</loc>
  <lastmod>2026-04-22T14:24:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サーキット中心量子分類器（Circuit-centric quantum classifiers）</news:title>
   <news:publication_date>2026-04-22T14:24:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682228</loc>
  <lastmod>2026-04-22T14:24:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MegaDepth: インターネット写真から学ぶ単眼深度推定（MegaDepth: Learning Single-View Depth Prediction from Internet Photos）</news:title>
   <news:publication_date>2026-04-22T14:24:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682226</loc>
  <lastmod>2026-04-22T14:24:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトウェア工数見積りにSBSEが必要な理由（Why Software Effort Estimation Needs SBSE）</news:title>
   <news:publication_date>2026-04-22T14:24:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682224</loc>
  <lastmod>2026-04-22T14:24:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>古典的多次元尺度構成の中心極限定理（Central Limit Theorems for Classical Multidimensional Scaling）</news:title>
   <news:publication_date>2026-04-22T14:24:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682222</loc>
  <lastmod>2026-04-22T13:32:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>世界を観察して学ぶ内在画像分解（Learning Intrinsic Image Decomposition from Watching the World）</news:title>
   <news:publication_date>2026-04-22T13:32:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682220</loc>
  <lastmod>2026-04-22T13:24:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮センシングによる分布整合の新展開（A Compressed Sensing Approach for Distribution Matching）</news:title>
   <news:publication_date>2026-04-22T13:24:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682218</loc>
  <lastmod>2026-04-22T13:23:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TacticToe: 定理証明を“戦術レベル”で学ぶ自動証明器（TacticToe: Learning to Prove with Tactics）</news:title>
   <news:publication_date>2026-04-22T13:23:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682216</loc>
  <lastmod>2026-04-22T13:23:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TacticToeが示した定理証明支援の新しい道（TacticToe: Learning to reason with HOL4 Tactics）</news:title>
   <news:publication_date>2026-04-22T13:23:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682214</loc>
  <lastmod>2026-04-22T13:22:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Average Biased ReLU による顔特徴量強化（Average Biased ReLU Based CNN Descriptor for Improved Face Retrieval）</news:title>
   <news:publication_date>2026-04-22T13:22:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682212</loc>
  <lastmod>2026-04-22T13:22:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D形状の記述子ネットワークが切り拓く立体モデリングの確率的アプローチ（Learning Descriptor Networks for 3D Shape Synthesis and Analysis）</news:title>
   <news:publication_date>2026-04-22T13:22:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682210</loc>
  <lastmod>2026-04-22T13:21:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチレイヤ複合ネットワークによる色-テクスチャ記述（Multilayer Complex Network Descriptors for Color-Texture Characterization）</news:title>
   <news:publication_date>2026-04-22T13:21:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682208</loc>
  <lastmod>2026-04-22T12:30:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>領域優先度を持つ自己符号化器による異常検知（Regional Priority based Anomaly Detection using Autoencoders）</news:title>
   <news:publication_date>2026-04-22T12:30:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682206</loc>
  <lastmod>2026-04-22T12:29:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高密度核物質中でのグルーオン放出の理論解析（Medium-induced gluon emission via transverse and longitudinal scattering in dense nuclear matter）</news:title>
   <news:publication_date>2026-04-22T12:29:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682204</loc>
  <lastmod>2026-04-22T12:29:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Database as a Serviceの現状と将来展望（Database as a Service - Current Issues and Its Future）</news:title>
   <news:publication_date>2026-04-22T12:29:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682202</loc>
  <lastmod>2026-04-22T12:27:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2次元ヒストグラム間のWasserstein距離計算を高速化する流れ（On the Computation of Kantorovich-Wasserstein Distances between 2D-Histograms）</news:title>
   <news:publication_date>2026-04-22T12:27:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682200</loc>
  <lastmod>2026-04-22T12:27:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>好奇心駆動探索による地図なしナビゲーション（Curiosity-driven Exploration for Mapless Navigation with Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-22T12:27:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682198</loc>
  <lastmod>2026-04-22T12:27:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Neural Networkを用いたBelief Propagation改善（Improving Massive MIMO Belief Propagation Detector with Deep Neural Network）</news:title>
   <news:publication_date>2026-04-22T12:27:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682196</loc>
  <lastmod>2026-04-22T12:27:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異なるサイズのオフライン手書き署名からの固定長表現学習（Fixed-sized representation learning from Offline Handwritten Signatures of different sizes）</news:title>
   <news:publication_date>2026-04-22T12:27:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682194</loc>
  <lastmod>2026-04-22T11:34:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報的不正取引の価値（THE VALUE OF INFORMATIONAL ARBITRAGE）</news:title>
   <news:publication_date>2026-04-22T11:34:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682192</loc>
  <lastmod>2026-04-22T11:34:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イオン結晶の赤外線スペクトルと統計力学との関連（Classical infrared spectra of ionic crystals and their relevance for statistical mechanics）</news:title>
   <news:publication_date>2026-04-22T11:34:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682190</loc>
  <lastmod>2026-04-22T11:33:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>mQAPVizによる大規模データ可視化の革新（mQAPViz: A divide-and-conquer multi-objective optimization algorithm to compute large data visualizations）</news:title>
   <news:publication_date>2026-04-22T11:33:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682188</loc>
  <lastmod>2026-04-22T11:33:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>加速MRIのための深層残差学習（Deep Residual Learning for Accelerated MRI using Magnitude and Phase Networks）</news:title>
   <news:publication_date>2026-04-22T11:33:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682186</loc>
  <lastmod>2026-04-22T11:33:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケールに強い物体検出で何が変わるか（SINet: A Scale-insensitive Convolutional Neural Network for Fast Vehicle Detection）</news:title>
   <news:publication_date>2026-04-22T11:33:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/682184</loc>
  <lastmod>2026-04-22T11:32:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>環境を探索して学習する視覚的顕著性の獲得（Exploring to learn visual saliency: The RL-IAC approach）</news:title>
   <news:publication_date>2026-04-22T11:32:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682182</loc>
  <lastmod>2026-04-22T11:32:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を用いた車両検出の実務的意義（A Vehicle Detection Approach using Deep Learning Methodologies）</news:title>
   <news:publication_date>2026-04-22T11:32:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682180</loc>
  <lastmod>2026-04-22T10:41:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SyncGANによるクロスモーダル生成の同期化（SyncGAN: Synchronize the Latent Space of Cross-modal Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-04-22T10:41:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682178</loc>
  <lastmod>2026-04-22T10:33:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケール位置認識カーネル表現による物体検出（Multi-scale Location-aware Kernel Representation for Object Detection）</news:title>
   <news:publication_date>2026-04-22T10:33:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682176</loc>
  <lastmod>2026-04-22T10:32:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非並列データを用いた高品質な音声変換（HIGH-QUALITY NONPARALLEL VOICE CONVERSION BASED ON CYCLE-CONSISTENT ADVERSARIAL NETWORK）</news:title>
   <news:publication_date>2026-04-22T10:32:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/682174</loc>
  <lastmod>2026-04-22T10:32:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学生の学習技能をファジィ関係方程式で評価する手法（A STUDY OF STUDENT LEARNING SKILLS USING FUZZY RELATION EQUATIONS）</news:title>
   <news:publication_date>2026-04-22T10:32:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682172</loc>
  <lastmod>2026-04-22T10:31:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>KaldiのPLDA実装に関するメモ（A Note on Kaldi’s PLDA Implementation）</news:title>
   <news:publication_date>2026-04-22T10:31:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682170</loc>
  <lastmod>2026-04-22T10:31:09Z</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Gaussian ICAの再発見（Sparse Gaussian ICA）</news:title>
   <news:publication_date>2026-04-22T10:31:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682168</loc>
  <lastmod>2026-04-22T10:30:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画理解のためのエンドツーエンド運動表現学習（End-to-End Learning of Motion Representation for Video Understanding）</news:title>
   <news:publication_date>2026-04-22T10:30:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682166</loc>
  <lastmod>2026-04-22T09:39:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>好中球の生成的時空間モデリング（Generative Spatiotemporal Modeling Of Neutrophil Behavior）</news:title>
   <news:publication_date>2026-04-22T09:39:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682164</loc>
  <lastmod>2026-04-22T09:38:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データベース用エンドツーエンドニューラル自然言語インターフェース（DBPal: An End-to-end Neural Natural Language Interface for Databases）</news:title>
   <news:publication_date>2026-04-22T09:38:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682162</loc>
  <lastmod>2026-04-22T09:36:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2Dと3Dの橋渡しをする軽量3D融合ネットワーク（Bridging the Gap Between 2D and 3D Organ Segmentation with Volumetric Fusion Net）</news:title>
   <news:publication_date>2026-04-22T09:36:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682160</loc>
  <lastmod>2026-04-22T09:36:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構を用いたアンサンブルによる深層距離学習の改良（Attention-based Ensemble for Deep Metric Learning）</news:title>
   <news:publication_date>2026-04-22T09:36:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682158</loc>
  <lastmod>2026-04-22T09:36:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習可能な辞書符号化層によるエンドツーエンド音声言語識別（A NOVEL LEARNABLE DICTIONARY ENCODING LAYER FOR END-TO-END LANGUAGE IDENTIFICATION）</news:title>
   <news:publication_date>2026-04-22T09:36:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682156</loc>
  <lastmod>2026-04-22T09:36:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>終端学習が言語識別を変える――話者属性の「発話単位表現」へ挑む（INSIGHTS INTO END-TO-END LEARNING SCHEME FOR LANGUAGE IDENTIFICATION）</news:title>
   <news:publication_date>2026-04-22T09:36:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682154</loc>
  <lastmod>2026-04-22T09:36:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インフラ施設の防護投資の最適化（Securing Infrastructure Facilities: When does proactive defense help?）</news:title>
   <news:publication_date>2026-04-22T09:36:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682152</loc>
  <lastmod>2026-04-22T08:42:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人物検索のための検出と再識別を統合したエンドツーエンドネットワーク（End-to-End Detection and Re-identification Integrated Net for Person Search）</news:title>
   <news:publication_date>2026-04-22T08:42:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682150</loc>
  <lastmod>2026-04-22T08:42:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運動学的筋骨格環境に適応させた強化学習の実践（Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments）</news:title>
   <news:publication_date>2026-04-22T08:42:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682148</loc>
  <lastmod>2026-04-22T08:42:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リコールトレース：バックトラッキングモデルによる効率的強化学習（RECALL TRACES: BACKTRACKING MODELS FOR EFFICIENT REINFORCEMENT LEARNING）</news:title>
   <news:publication_date>2026-04-22T08:42:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682146</loc>
  <lastmod>2026-04-22T08:41:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変数射影によるスパース主成分分析（Sparse Principal Component Analysis via Variable Projection）</news:title>
   <news:publication_date>2026-04-22T08:41:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682144</loc>
  <lastmod>2026-04-22T08:41:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>社会的学習に基づく頑健なデータ融合（Social learning for resilient data fusion against data falsification attacks）</news:title>
   <news:publication_date>2026-04-22T08:41:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682142</loc>
  <lastmod>2026-04-22T08:41:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱い指導情報を取り込む回帰の確率的枠組み（Probabilistic Formulations of Regression with Mixed Guidance）</news:title>
   <news:publication_date>2026-04-22T08:41:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682140</loc>
  <lastmod>2026-04-22T08:41:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし相関解析（Unsupervised Correlation Analysis）</news:title>
   <news:publication_date>2026-04-22T08:41:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682138</loc>
  <lastmod>2026-04-22T07:49:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高移動環境における車載ネットワークと機械学習の枠組み（Towards Intelligent Vehicular Networks: A Machine Learning Framework）</news:title>
   <news:publication_date>2026-04-22T07:49:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682136</loc>
  <lastmod>2026-04-22T07:49:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ構造化フィードバック下のオンライン学習と適応的敵対者への対策（Online learning with graph-structured feedback against adaptive adversaries）</news:title>
   <news:publication_date>2026-04-22T07:49:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682134</loc>
  <lastmod>2026-04-22T07:49:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>代用教師ネットワークの考え方と示唆（Substitute Teacher Networks: Learning with Almost No Supervision）</news:title>
   <news:publication_date>2026-04-22T07:49:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682132</loc>
  <lastmod>2026-04-22T07:49:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>完全に教師なしで音素を認識する手法の要点（Completely Unsupervised Phoneme Recognition by Adversarially Learning Mapping Relationships from Audio Embeddings）</news:title>
   <news:publication_date>2026-04-22T07:49:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682130</loc>
  <lastmod>2026-04-22T07:48:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習データを狙う攻撃と防御――線形回帰に対する汚染（Poisoning）攻撃の体系的研究（Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning）</news:title>
   <news:publication_date>2026-04-22T07:48:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682128</loc>
  <lastmod>2026-04-22T07:48:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話型音声コンテンツ検索の共同学習と学習可能ユーザシミュレータ（Joint Learning of Interactive Spoken Content Retrieval and Trainable User Simulator）</news:title>
   <news:publication_date>2026-04-22T07:48:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682126</loc>
  <lastmod>2026-04-22T07:48:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Aggregated Momentumによる最適化の安定化（AGGREGATED MOMENTUM: STABILITY THROUGH PASSIVE DAMPING）</news:title>
   <news:publication_date>2026-04-22T07:48:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682124</loc>
  <lastmod>2026-04-22T06:57:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SGNSの再考：二乗正則化によるスキップグラム負例学習の改良（Revisiting Skip-Gram Negative Sampling Model With Rectification）</news:title>
   <news:publication_date>2026-04-22T06:57:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682122</loc>
  <lastmod>2026-04-22T06:57:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頑健な果実計数（Robust Fruit Counting: Combining Deep Learning, Tracking, and Structure from Motion）</news:title>
   <news:publication_date>2026-04-22T06:57:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682120</loc>
  <lastmod>2026-04-22T06:57:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>術後CTAにおける腹部大動脈血栓の完全自動検出と分割（Fully automatic detection and segmentation of abdominal aortic thrombus in post-operative CTA images using deep convolutional neural networks）</news:title>
   <news:publication_date>2026-04-22T06:57:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682118</loc>
  <lastmod>2026-04-22T06:57:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EarthMapper: リモートセンシング画像の意味的セグメンテーションを手軽にするツールボックス（EarthMapper: A Tool Box for the Semantic Segmentation of Remote Sensing Imagery）</news:title>
   <news:publication_date>2026-04-22T06:57:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682116</loc>
  <lastmod>2026-04-22T06:56:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ上の注意型マルチラベル学習（Attentional Multilabel Learning over Graphs: A Message Passing Approach）</news:title>
   <news:publication_date>2026-04-22T06:56:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682114</loc>
  <lastmod>2026-04-22T06:56:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短発話のスピーカ認証を改善するi-vector変換（I-vector Transformation Using Conditional Generative Adversarial Networks for Short Utterance Speaker Verification）</news:title>
   <news:publication_date>2026-04-22T06:56:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/682112</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682110</loc>
  <lastmod>2026-04-22T06:05:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リモートセンシングにおける圧縮アーティファクト除去のOne‑Two‑Oneネットワーク（One‑Two‑One Networks for Compression Artifacts Reduction in Remote Sensing）</news:title>
   <news:publication_date>2026-04-22T06:05:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/682108</loc>
  <lastmod>2026-04-22T06:04:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SampleAheadによる合成データ学習の実践（SampleAhead: Online Classifier-Sampler Communication for Learning from Synthesized Data）</news:title>
   <news:publication_date>2026-04-22T06:04:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682106</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>スムーズな入力準備が拓く量子機械学習の現場応用（Smooth input preparation for quantum and quantum-inspired machine learning）</news:title>
   <news:publication_date>2026-04-22T06:04:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682104</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ対応の転送による人物再識別（Graph Correspondence Transfer for Person Re-identification）</news:title>
   <news:publication_date>2026-04-22T06:02:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682102</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>構造転送機械の理論と応用 (The Structure Transfer Machine Theory and Applications)</news:title>
   <news:publication_date>2026-04-22T06:02:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682100</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>ゲーム行動における個人差のモデル化（Modeling Individual Differences in Game Behavior using HMM）</news:title>
   <news:publication_date>2026-04-22T06:02:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682098</loc>
  <lastmod>2026-04-22T06:01:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Transformerモデルの学習ノウハウ（Training Tips for the Transformer Model）</news:title>
   <news:publication_date>2026-04-22T06:01:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682096</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>メカニズム型ネットワークモデルの柔軟なモデル選択（Flexible model selection for mechanistic network models）</news:title>
   <news:publication_date>2026-04-22T05:10:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682094</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>2026-04-22T05:09:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682092</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>2026-04-22T05:09:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682090</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>単純化された0ビット一貫重み付きサンプリングの工学（Engineering a Simplified 0-Bit Consistent Weighted Sampling）</news:title>
   <news:publication_date>2026-04-22T05:07:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682088</loc>
  <lastmod>2026-04-22T05:07:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ある種の関数最適化問題に関するいくつかの結果（Some results on a class of functional optimization problems）</news:title>
   <news:publication_date>2026-04-22T05:07:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682086</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模マルチタスク学習による汎用文分散表現学習（LEARNING GENERAL PURPOSE DISTRIBUTED SENTENCE REPRESENTATIONS VIA LARGE SCALE MULTI-TASK LEARNING）</news:title>
   <news:publication_date>2026-04-22T05:07:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-22T05:06:31Z</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>視覚に基づくロボットタスク計画（Visual Robot Task Planning）</news:title>
   <news:publication_date>2026-04-22T04:15:25Z</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>部分クラス選択による転移学習の最適化（Class Subset Selection for Transfer Learning using Submodularity）</news:title>
   <news:publication_date>2026-04-22T04:14:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-22T04:14:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682076</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>階層的転移畳み込みニューラルネットワーク（Hierarchical Transfer Convolutional Neural Networks for Image Classification）</news:title>
   <news:publication_date>2026-04-22T04:13:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682074</loc>
  <lastmod>2026-04-22T04:13:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付きエンドツーエンド音声変換（Conditional End-to-End Audio Transforms）</news:title>
   <news:publication_date>2026-04-22T04:13:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682072</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>リアルタイム多指ハンドの把持計画：フィンガースプリッティング法 (Real-Time Grasp Planning for Multi-Fingered Hands by Finger Splitting)</news:title>
   <news:publication_date>2026-04-22T04:12:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-22T04:12:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682068</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンド音声処理の実用プラットフォームの要点（ESPnet: End-to-End Speech Processing Toolkit）</news:title>
   <news:publication_date>2026-04-22T03:20:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682066</loc>
  <lastmod>2026-04-22T03:20:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己組織化されたヒッグス臨界性（Self-Organized Higgs Criticality）</news:title>
   <news:publication_date>2026-04-22T03:20:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682064</loc>
  <lastmod>2026-04-22T03:19:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MRベースの電気特性トモグラフィに深層学習を開く（Opening a new window on MR-based Electrical Properties Tomography with deep learning）</news:title>
   <news:publication_date>2026-04-22T03:19:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682062</loc>
  <lastmod>2026-04-22T03:19:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ブロックモデルの固有値が示すもの（THE EIGENVALUES OF STOCHASTIC BLOCKMODEL GRAPHS）</news:title>
   <news:publication_date>2026-04-22T03:19:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682060</loc>
  <lastmod>2026-04-22T03:18:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔匿名化によるプライバシー保護付き行動検出の学習（Learning to Anonymize Faces for Privacy Preserving Action Detection）</news:title>
   <news:publication_date>2026-04-22T03:18:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682058</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>上向きANITA事象とCPT対称宇宙（Upgoing ANITA events as evidence of the CPT symmetric universe）</news:title>
   <news:publication_date>2026-04-22T03:18:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682056</loc>
  <lastmod>2026-04-22T03:18:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全データにおけるマルチモーダル疾患分類の幾何行列補完（Multi-modal Disease Classification in Incomplete Datasets Using Geometric Matrix Completion）</news:title>
   <news:publication_date>2026-04-22T03:18:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682054</loc>
  <lastmod>2026-04-22T02:26:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言葉でCNNを導く――対話による視覚モデルの性能改善（Guide Me: Interacting with Deep Networks）</news:title>
   <news:publication_date>2026-04-22T02:26:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682052</loc>
  <lastmod>2026-04-22T02:26:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソルネットワークを用いた量子機械学習の展望（Towards Quantum Machine Learning with Tensor Networks）</news:title>
   <news:publication_date>2026-04-22T02:26:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682050</loc>
  <lastmod>2026-04-22T02:26:16Z</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>2026-04-22T02:26:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682048</loc>
  <lastmod>2026-04-22T02:25:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>野外物体の3D姿勢推定と3Dモデル取得（3D Pose Estimation and 3D Model Retrieval for Objects in the Wild）</news:title>
   <news:publication_date>2026-04-22T02:25:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682046</loc>
  <lastmod>2026-04-22T02:24:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル音声表現の再利用による聴覚感情認識（Reusing Neural Speech Representations for Auditory Emotion Recognition）</news:title>
   <news:publication_date>2026-04-22T02:24:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-22T02:24:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QMIX: 中央集権的学習で分散実行を可能にした価値関数分解（QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-22T02:24:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-04-22T02:24:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>オンライン教師あり学習と特徴選択の新しい枠組み（A Novel Framework for Online Supervised Learning with Feature Selection）</news:title>
   <news:publication_date>2026-04-22T02:24:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682040</loc>
  <lastmod>2026-04-22T01:32:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観測器ベースの適応最適出力包含制御（Observer-based Adaptive Optimal Output Containment Control problem of Linear Heterogeneous Multi-agent Systems with Relative Output Measurements）</news:title>
   <news:publication_date>2026-04-22T01:32:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682038</loc>
  <lastmod>2026-04-22T01:23:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二乗型フーリエ関数解析における最小最大推定（Minimax Estimation of Quadratic Fourier Functionals）</news:title>
   <news:publication_date>2026-04-22T01:23:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682036</loc>
  <lastmod>2026-04-22T01:23:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模化するロゴ検出のための自動学習手法（Scalable Deep Learning Logo Detection）</news:title>
   <news:publication_date>2026-04-22T01:23:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682034</loc>
  <lastmod>2026-04-22T01:23:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボット把持検出のための大規模合成データセットの意義（Jacquard: A Large Scale Dataset for Robotic Grasp Detection）</news:title>
   <news:publication_date>2026-04-22T01:23:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682032</loc>
  <lastmod>2026-04-22T01:22:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分割ポテンシャル箱におけるPT対称と反対称の非線形状態（PT-symmetric and antisymmetric nonlinear states in a split potential box）</news:title>
   <news:publication_date>2026-04-22T01:22:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682030</loc>
  <lastmod>2026-04-22T01:22:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>K-NNとDNNにおけるラベルノイズの耐性（Label Noise in K-NN and DNN）</news:title>
   <news:publication_date>2026-04-22T01:22:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682028</loc>
  <lastmod>2026-04-22T01:22:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小サンプル学習のためのCNNフィルタの構造と強さの学習（Learning Structure and Strength of CNN Filters for Small Sample Size Training）</news:title>
   <news:publication_date>2026-04-22T01:22:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682026</loc>
  <lastmod>2026-04-22T00:31:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスモーダル深層変分手位姿推定（Cross-modal Deep Variational Hand Pose Estimation）</news:title>
   <news:publication_date>2026-04-22T00:31:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682024</loc>
  <lastmod>2026-04-22T00:30:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コントラスト志向の深層ニューラルネットワークによる顕在物体検出（Contrast-Oriented Deep Neural Networks for Salient Object Detection）</news:title>
   <news:publication_date>2026-04-22T00:30:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682022</loc>
  <lastmod>2026-04-22T00:30:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非局所相似性とモデル導関数領域適応スパース正則化を用いたフルウェーブフォーム反転（Full waveform inversion with nonlocal similarity and model-derivative domain adaptive sparsity-promoting regularization）</news:title>
   <news:publication_date>2026-04-22T00:30:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682020</loc>
  <lastmod>2026-04-22T00:29:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習によって分類器を生成する手法（Learning to generate classifiers）</news:title>
   <news:publication_date>2026-04-22T00:29:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682018</loc>
  <lastmod>2026-04-22T00:29:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列グリッドプーリングによるデータ拡張（Parallel Grid Pooling for Data Augmentation）</news:title>
   <news:publication_date>2026-04-22T00:29:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682016</loc>
  <lastmod>2026-04-22T00:29:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D顔形状における特徴の分離による同時再構成と認識（Disentangling Features in 3D Face Shapes for Joint Face Reconstruction and Recognition）</news:title>
   <news:publication_date>2026-04-22T00:29:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682014</loc>
  <lastmod>2026-04-22T00:28:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械的文章理解のためのニューロモデル訓練（The Training of Neuromodels for Machine Comprehension of Text）</news:title>
   <news:publication_date>2026-04-22T00:28:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682012</loc>
  <lastmod>2026-04-21T23:37:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イベントログから学習者行動パターンを発見する（Discovering Student Behavior Patterns from Event Logs: Preliminary Results on A Novel Probabilistic Latent Variable Model）</news:title>
   <news:publication_date>2026-04-21T23:37:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682010</loc>
  <lastmod>2026-04-21T23:37:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分岐するプログラムを微分可能にするDDRフレームワーク（DDRprog: A CLEVR Differentiable Dynamic Reasoning Programmer）</news:title>
   <news:publication_date>2026-04-21T23:37:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682008</loc>
  <lastmod>2026-04-21T23:36:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズラベル下での共同最適化フレームワーク（Joint Optimization Framework for Learning with Noisy Labels）</news:title>
   <news:publication_date>2026-04-21T23:36:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682006</loc>
  <lastmod>2026-04-21T23:36:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的な現実環境での迅速適応を学ぶ（LEARNING TO ADAPT IN DYNAMIC, REAL-WORLD ENVIRONMENTS THROUGH META-REINFORCEMENT LEARNING）</news:title>
   <news:publication_date>2026-04-21T23:36:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682004</loc>
  <lastmod>2026-04-21T23:35:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視点特化型ディープネットワークによる人物再識別（Learning View-Specific Deep Networks for Person Re-Identification）</news:title>
   <news:publication_date>2026-04-21T23:35:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682002</loc>
  <lastmod>2026-04-21T23:35:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多階層類似度による効率的な人物再識別（Efficient and Deep Person Re-Identification using Multi-Level Similarity）</news:title>
   <news:publication_date>2026-04-21T23:35:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682000</loc>
  <lastmod>2026-04-21T23:35:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>キャッシュ対応型動的ビットレート配分と深い自己転移強化学習（Cache-Enabled Dynamic Rate Allocation via Deep Self-Transfer Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-21T23:35:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681998</loc>
  <lastmod>2026-04-21T22:44:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移的バイアス除去埋め込みによるゼロショット学習の改良（Transductive Unbiased Embedding for Zero-Shot Learning）</news:title>
   <news:publication_date>2026-04-21T22:44:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681996</loc>
  <lastmod>2026-04-21T22:43:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインショッピングアシスタントにおける深いカスケード型マルチタスク学習（Deep Cascade Multi-task Learning for Slot Filling in Online Shopping Assistant）</news:title>
   <news:publication_date>2026-04-21T22:43:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681994</loc>
  <lastmod>2026-04-21T22:43:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体検出を目指したタスク駆動型超解像（Task-Driven Super Resolution: Object Detection in Low-resolution Images）</news:title>
   <news:publication_date>2026-04-21T22:43:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681992</loc>
  <lastmod>2026-04-21T22:42:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒューマンロボット協調のためのPOMDPモデル学習（POMDP Model Learning for Human Robot Collaboration）</news:title>
   <news:publication_date>2026-04-21T22:42:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681990</loc>
  <lastmod>2026-04-21T22:42:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ストレージ問題のシミュレーション手法（Simulation Methods for Stochastic Storage Problems: A Statistical Learning Perspective）</news:title>
   <news:publication_date>2026-04-21T22:42:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681988</loc>
  <lastmod>2026-04-21T22:42:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>膵臓のCT/MRI画像におけるセグメンテーション手法の統合的改良（Pancreas Segmentation in CT and MRI Images via Domain Specific Network Designing and Recurrent Neural Contextual Learning）</news:title>
   <news:publication_date>2026-04-21T22:42:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681986</loc>
  <lastmod>2026-04-21T22:42:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベルフリー自動蛍光を用いた深層学習による仮想組織染色（Deep learning-based virtual histology staining using auto-fluorescence of label-free tissue）</news:title>
   <news:publication_date>2026-04-21T22:42:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681984</loc>
  <lastmod>2026-04-21T21:50:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>依存構文コンテキストを用いた頑健なクロスリンガル上位語検出（Robust Cross-lingual Hypernymy Detection using Dependency Context）</news:title>
   <news:publication_date>2026-04-21T21:50:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681982</loc>
  <lastmod>2026-04-21T21:50:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観測と特徴が同時に分散された大規模学習の確率的手法（Stochastic Large-scale Machine Learning Algorithms with Distributed Features and Observations）</news:title>
   <news:publication_date>2026-04-21T21:50:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681980</loc>
  <lastmod>2026-04-21T21:49:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>商品属性抽出における深層再帰ニューラルネットワーク（Deep Recurrent Neural Networks for Product Attribute Extraction in eCommerce）</news:title>
   <news:publication_date>2026-04-21T21:49:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681978</loc>
  <lastmod>2026-04-21T21:49:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプリングと時間の不可分性が分子記録と化石記録の統合に与える影響（THE INSEPARABILITY OF SAMPLING AND TIME AND ITS INFLUENCE ON ATTEMPTS TO UNIFY THE MOLECULAR AND FOSSIL RECORDS）</news:title>
   <news:publication_date>2026-04-21T21:49:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681976</loc>
  <lastmod>2026-04-21T21:48:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像誘導下動作学習における速さと正確さのトレードオフ（Getting nowhere fast: trade-off between speed and precision in training to execute image-guided hand-tool movements）</news:title>
   <news:publication_date>2026-04-21T21:48:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681974</loc>
  <lastmod>2026-04-21T21:48:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>古典データを量子系で学習する意義（Learning quantum models from quantum or classical data）</news:title>
   <news:publication_date>2026-04-21T21:48:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681972</loc>
  <lastmod>2026-04-21T21:48:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経路知識を組み込むことで解釈性と汎化性を高める機械学習手法（PIMKL: Pathway Induced Multiple Kernel Learning）</news:title>
   <news:publication_date>2026-04-21T21:48:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681970</loc>
  <lastmod>2026-04-21T20:57:27Z</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>2026-04-21T20:57:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間データを用いた統計・機械学習モデルの性能評価とハイパーパラメータ調整（Performance evaluation and hyperparameter tuning of statistical and machine-learning models using spatial data）</news:title>
   <news:publication_date>2026-04-21T20:57:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的信号除去のための効率的な一次アルゴリズム（Efficient First-Order Algorithms for Adaptive Signal Denoising）</news:title>
   <news:publication_date>2026-04-21T20:57:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681964</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>核内のエキゾチックなグルーオン状態の探索（Search for Exotic Gluonic States in the Nucleus）</news:title>
   <news:publication_date>2026-04-21T20:56:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681962</loc>
  <lastmod>2026-04-21T20:56:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファインチューニング不要の転移学習改善（Improve the performance of transfer learning without fine-tuning using dissimilarity-based multi-view learning for breast cancer histology images）</news:title>
   <news:publication_date>2026-04-21T20:56:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681960</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>2Dレーザレンジデータのみを用いたパレット検出・局所化・追跡（Pallet Detection, Localisation and Tracking using 2D Range Data）</news:title>
   <news:publication_date>2026-04-21T20:55:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像概念を用いたテキストグラウンディングの解釈可能でグローバル最適な予測（Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts）</news:title>
   <news:publication_date>2026-04-21T20:55:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681956</loc>
  <lastmod>2026-04-21T20:04:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MemGEN: 記憶に基づく生成モデルの寓話（MemGEN: Memory is All You Need）</news:title>
   <news:publication_date>2026-04-21T20:04:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681954</loc>
  <lastmod>2026-04-21T20:03:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MaskRNNによるインスタンスレベル動画物体セグメンテーション（MaskRNN: Instance Level Video Object Segmentation）</news:title>
   <news:publication_date>2026-04-21T20:03:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681952</loc>
  <lastmod>2026-04-21T20:03:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なしテキストグラウンディング（Unsupervised Textual Grounding: Linking Words to Image Concepts）</news:title>
   <news:publication_date>2026-04-21T20:03:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681950</loc>
  <lastmod>2026-04-21T20:02:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的勾配ハミルトンモンテカルロの分散低減によるベイズ推論の改善（Stochastic Gradient Hamiltonian Monte Carlo with Variance Reduction for Bayesian Inference）</news:title>
   <news:publication_date>2026-04-21T20:02:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681948</loc>
  <lastmod>2026-04-21T20:02:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子ニューラルネットワークの訓練における『不毛地帯（Barren Plateaus）』問題（Barren plateaus in quantum neural network training landscapes）</news:title>
   <news:publication_date>2026-04-21T20:02:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681946</loc>
  <lastmod>2026-04-21T20:01:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文を数値ベクトルに変える技術の実務的意義（Universal Sentence Encoder）</news:title>
   <news:publication_date>2026-04-21T20:01:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681944</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>深層学習を用いた画像フォレンジクスの安全性検討（Security Consideration For Deep Learning-Based Image Forensics）</news:title>
   <news:publication_date>2026-04-21T20:01:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681942</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>銀河と大規模構造の分類に向けた機械学習的アプローチ（A Machine Learning Approach to Galaxy-LSS Classification I: Imprints on Halo Merger Trees）</news:title>
   <news:publication_date>2026-04-21T19:10:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681940</loc>
  <lastmod>2026-04-21T19:09:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組込み機器における詳細なエネルギー・性能プロファイリング手法（Fine-Grained Energy and Performance Profiling framework for Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-04-21T19:09:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681938</loc>
  <lastmod>2026-04-21T19:08:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SPAREによる運動学記述学習（Learning Kinematic Descriptions using SPARE）</news:title>
   <news:publication_date>2026-04-21T19:08:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681936</loc>
  <lastmod>2026-04-21T19:07:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>色のない緑の再帰的ネットワークは階層的に夢を見る（Colorless green recurrent networks dream hierarchically）</news:title>
   <news:publication_date>2026-04-21T19:07:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681934</loc>
  <lastmod>2026-04-21T19:07:27Z</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>2026-04-21T19:07:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681932</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>計算困難性と統計的可能性のギャップの予測（NOTES ON COMPUTATIONAL-TO-STATISTICAL GAPS: PREDICTIONS USING STATISTICAL PHYSICS）</news:title>
   <news:publication_date>2026-04-21T19:06:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681930</loc>
  <lastmod>2026-04-21T19:06:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特権情報（LUPI）とSVM+が早期創薬にもたらすもの（Application of SVM+ in Early Drug Discovery）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681928</loc>
  <lastmod>2026-04-21T18:15:19Z</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>2026-04-21T18:15:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681926</loc>
  <lastmod>2026-04-21T18:07:37Z</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/681924</loc>
  <lastmod>2026-04-21T18:05:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習による信号制御の要点解説（Deep Reinforcement Learning for Traffic Light Control in Vehicular Networks）</news:title>
   <news:publication_date>2026-04-21T18:05:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681922</loc>
  <lastmod>2026-04-21T18:03:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頻出アイテム集合採掘におけるユビキタスアイテムの除去（Frequent Item-set Mining without Ubiquitous Items）</news:title>
   <news:publication_date>2026-04-21T18:03:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681920</loc>
  <lastmod>2026-04-21T18:02:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mining on Manifolds: Metric Learning without Labels（Mining on Manifolds: Metric Learning without Labels）</news:title>
   <news:publication_date>2026-04-21T18:02:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681918</loc>
  <lastmod>2026-04-21T18:02:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3次元で整合性のある両心室心筋セグメンテーションによるメッシュ生成（3D Consistent Biventricular Myocardial Segmentation Using Deep Learning for Mesh Generation）</news:title>
   <news:publication_date>2026-04-21T18:02:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681916</loc>
  <lastmod>2026-04-21T18:01:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔のなりすまし検出における二値監督と補助的監督の比較（Learning Deep Models for Face Anti-Spoofing: Binary or Auxiliary Supervision）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681914</loc>
  <lastmod>2026-04-21T17:10:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>COBRAS: 高速反復型ペアワイズ制約アクティブクラスタリング（COBRAS: Fast, Iterative, Active Clustering with Pairwise Constraints）</news:title>
   <news:publication_date>2026-04-21T17:10:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681912</loc>
  <lastmod>2026-04-21T17:10:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CobWebによるトモグラフィー画像自動解析の実装と応用（CobWeb ― a toolbox for automatic tomographic image analysis based on machine learning techniques: application and examples）</news:title>
   <news:publication_date>2026-04-21T17:10:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681910</loc>
  <lastmod>2026-04-21T17:09:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化注意付き畳み込みニューラル場による単眼深度推定（Structured Attention Guided Convolutional Neural Fields for Monocular Depth Estimation）</news:title>
   <news:publication_date>2026-04-21T17:09:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681908</loc>
  <lastmod>2026-04-21T17:08:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタアンサンブルに基づくハイパーパラメータ探索（On Hyperparameter Search in Cluster Ensembles）</news:title>
   <news:publication_date>2026-04-21T17:08:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681906</loc>
  <lastmod>2026-04-21T17:08:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習ベースのマルチホップ経路探索でLPWANの省エネを実現する（Towards Energy Efficient LPWANs through Learning-based Multi-hop Routing）</news:title>
   <news:publication_date>2026-04-21T17:08:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/681904</loc>
  <lastmod>2026-04-21T17:08:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>属性重み付きSMOTEの改良：相互情報量と多様なエントロピーの適用（Modified SMOTE Using Mutual Information and Different Sorts of Entropies）</news:title>
   <news:publication_date>2026-04-21T17:08:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681902</loc>
  <lastmod>2026-04-21T17:07:24Z</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>2026-04-21T17:07:24Z</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>ジヒドロール角予測にGANを適用する研究（Dihedral angle prediction using generative adversarial networks）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Winograd畳み込みの誤差解析と精度改善（ERROR ANALYSIS AND IMPROVING THE ACCURACY OF WINOGRAD CONVOLUTION FOR DEEP NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-04-21T16:15:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681896</loc>
  <lastmod>2026-04-21T16:15:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クローン防御による深層学習の安全性強化（Protection against Cloning for Deep Learning）</news:title>
   <news:publication_date>2026-04-21T16:15:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681894</loc>
  <lastmod>2026-04-21T16:14:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意力付き統計プーリングによる深層話者埋め込み（Attentive Statistics Pooling for Deep Speaker Embedding）</news:title>
   <news:publication_date>2026-04-21T16:14:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681892</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>電子イオン衝突型加速器における二ジェット光生成で核のパートン分布関数を測る可能性（Nuclear parton density functions from dijet photoproduction at the EIC）</news:title>
   <news:publication_date>2026-04-21T16:13:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681890</loc>
  <lastmod>2026-04-21T16:13:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プロトンドリップラインを越えた探査：アルゴンと塩素同位体鎖の新知見（Deep excursion beyond the proton dripline. I. Argon and chlorine isotope chains）</news:title>
   <news:publication_date>2026-04-21T16:13:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681888</loc>
  <lastmod>2026-04-21T16:13:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延フィードバック下の最良腕同定（Best arm identification in multi-armed bandits with delayed feedback）</news:title>
   <news:publication_date>2026-04-21T16:13:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681886</loc>
  <lastmod>2026-04-21T15:22:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>B-DCGANによるFPGA実装の評価（B-DCGAN: Evaluation of Binarized DCGAN for FPGA）</news:title>
   <news:publication_date>2026-04-21T15:22:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681884</loc>
  <lastmod>2026-04-21T15:22:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習による自由形状変形を用いた3D物体再構築（Learning Free-Form Deformations for 3D Object Reconstruction）</news:title>
   <news:publication_date>2026-04-21T15:22:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681882</loc>
  <lastmod>2026-04-21T15:21:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語モデリングのためのLPベースハイパーパラメータ最適化（An LP-based hyperparameter optimization model for language modeling）</news:title>
   <news:publication_date>2026-04-21T15:21:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681880</loc>
  <lastmod>2026-04-21T15:20:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブモジュラ・ラプラシアン系の多項式時間アルゴリズム（Polynomial-Time Algorithms for Submodular Laplacian Systems）</news:title>
   <news:publication_date>2026-04-21T15:20:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681878</loc>
  <lastmod>2026-04-21T15:20:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な人物再識別のための敵対的バイナリ符号化（Adversarial Binary Coding for Efficient Person Re-identification）</news:title>
   <news:publication_date>2026-04-21T15:20:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681876</loc>
  <lastmod>2026-04-21T15:20:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチビーム深層アトラクタネットワークによるカクテルパーティ問題の打破（Cracking the Cocktail Party Problem by Multi-Beam Deep Attractor Network）</news:title>
   <news:publication_date>2026-04-21T15:20:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681874</loc>
  <lastmod>2026-04-21T15:19:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小規模音声キーワード検出における注意機構終端モデル（Attention-based End-to-End Models for Small-Footprint Keyword Spotting）</news:title>
   <news:publication_date>2026-04-21T15:19:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681872</loc>
  <lastmod>2026-04-21T14:28:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行列積演算子を用いた系列から系列への学習（Matrix Product Operators for Sequence to Sequence Learning）</news:title>
   <news:publication_date>2026-04-21T14:28:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681870</loc>
  <lastmod>2026-04-21T14:28:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による教師なし顕著領域検出：複数ノイズラベリング視点（Deep Unsupervised Saliency Detection: A Multiple Noisy Labeling Perspective）</news:title>
   <news:publication_date>2026-04-21T14:28:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681868</loc>
  <lastmod>2026-04-21T14:28:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマート交通における汎用データ源の応用調査（Transport-domain applications of widely used data sources in the smart transportation: A survey）</news:title>
   <news:publication_date>2026-04-21T14:28:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681866</loc>
  <lastmod>2026-04-21T14:26:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地表テクスチャの深層マニホールド (Deep Texture Manifold for Ground Terrain Recognition)</news:title>
   <news:publication_date>2026-04-21T14:26:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681864</loc>
  <lastmod>2026-04-21T14:26:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ステガノグラフィに対するCNNベース検出器の弱点を突く手法（Weakening the Detecting Capability of CNN-Based Steganalysis）</news:title>
   <news:publication_date>2026-04-21T14:26:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681862</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>C1,1関数クラス回帰の構造的リスク最小化（Structural Risk Minimization for C1,1(R^d) Regression）</news:title>
   <news:publication_date>2026-04-21T14:26:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681860</loc>
  <lastmod>2026-04-21T14:26:05Z</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>2026-04-21T14:26:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681858</loc>
  <lastmod>2026-04-21T13:34:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体の周囲を見て見えない部分を推定するトップビュー表現（Learning to Look around Objects for Top-View Representations of Outdoor Scenes）</news:title>
   <news:publication_date>2026-04-21T13:34:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681856</loc>
  <lastmod>2026-04-21T13:34:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>静止画像における表情認識の特徴選択と分類器設計（Manifold-Based Feature Selection for Facial Expression Recognition）</news:title>
   <news:publication_date>2026-04-21T13:34:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681854</loc>
  <lastmod>2026-04-21T13:34:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボットビジョンにおける深層学習手法の総説 (A Survey on Deep Learning Methods for Robot Vision)</news:title>
   <news:publication_date>2026-04-21T13:34:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681852</loc>
  <lastmod>2026-04-21T13:33:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>1日屋外フォトメトリックステレオ（Single Day Outdoor Photometric Stereo）</news:title>
   <news:publication_date>2026-04-21T13:33:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681850</loc>
  <lastmod>2026-04-21T13:33:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期オンライン動画表現のためのメモリワープ（Memory Warps for Learning Long-Term Online Video Representations）</news:title>
   <news:publication_date>2026-04-21T13:33:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681848</loc>
  <lastmod>2026-04-21T13:33:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数カメラでの多人数追跡と再識別の特徴学習（Features for Multi-Target Multi-Camera Tracking and Re-Identification）</news:title>
   <news:publication_date>2026-04-21T13:33:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681846</loc>
  <lastmod>2026-04-21T13:33:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適量子制御のガラス的相（Glassy Phase of Optimal Quantum Control）</news:title>
   <news:publication_date>2026-04-21T13:33:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681844</loc>
  <lastmod>2026-04-21T12:41:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半ランダム敵対者に対する非凸行列補完（Non-Convex Matrix Completion Against a Semi-Random Adversary）</news:title>
   <news:publication_date>2026-04-21T12:41:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681842</loc>
  <lastmod>2026-04-21T12:41:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生態系モニタリングにおける物体検出の実用化（Deep Learning Object Detection Methods for Ecological Camera Trap Data）</news:title>
   <news:publication_date>2026-04-21T12:41:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681840</loc>
  <lastmod>2026-04-21T12:41:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>基底関数変換による敵対的画像への防御（Defending against Adversarial Images using Basis Functions Transformations）</news:title>
   <news:publication_date>2026-04-21T12:41:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681838</loc>
  <lastmod>2026-04-21T12:40:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化重み行列に基づくハードウェアアクセラレータ（Structured Weight Matrices-Based Hardware Accelerators in Deep Neural Networks: FPGAs and ASICs）</news:title>
   <news:publication_date>2026-04-21T12:40:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681836</loc>
  <lastmod>2026-04-21T12:40:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一細胞セグメンテーションを簡潔にする深距離推定器と深層細胞検出器（Learn to segment single cells with deep distance estimator and deep cell detector）</news:title>
   <news:publication_date>2026-04-21T12:40:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681834</loc>
  <lastmod>2026-04-21T12:40:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散データ処理プラットフォームの使いやすさ比較（On the Usability of Hadoop MapReduce, Apache Spark &amp;amp; Apache Flink for Data Science）</news:title>
   <news:publication_date>2026-04-21T12:40:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681832</loc>
  <lastmod>2026-04-21T12:39:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的知識伝達による深層表現学習（Learning Deep Representations with Probabilistic Knowledge Transfer）</news:title>
   <news:publication_date>2026-04-21T12:39:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681830</loc>
  <lastmod>2026-04-21T11:48:46Z</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>2026-04-21T11:48:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-21T11:48:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴寄与の監督（Supervising Feature Influence）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-04-21T11:48:17Z</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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    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>局所接続通信網を用いた電力網電圧制御のための分散均衡学習 (Distributed Equilibrium-Learning for Power Network Voltage Control With a Locally Connected Communication Network)</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-21T10:55:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-21T10:54:44Z</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>2026-04-21T10:54:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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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>2026-04-21T10:53:43Z</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>2026-04-21T10:02:43Z</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>2026-04-21T10:02:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-21T10:00:26Z</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>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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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>2026-04-21T08:56:31Z</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>2026-04-21T08:56:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-21T08:04:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-21T08:02:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-21T08:02:17Z</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>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-04-21T07:08:30Z</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>
   </news:publication>
   <news:title>3D-SIMDプロセッサをFPGAで実装して省メモリ・高速化を図る手法（FPGA Implementations of 3D-SIMD Processor Architecture for Deep Neural Networks Using Relative Indexed Compressed Sparse Filter Encoding Format and Stacked Filters Stationary Flow）</news:title>
   <news:publication_date>2026-04-21T07:08:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681752</loc>
  <lastmod>2026-04-21T07:07:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速ビジュアルトラッキングのための文脈認識深部特徴圧縮（Context-aware Deep Feature Compression for High-speed Visual Tracking）</news:title>
   <news:publication_date>2026-04-21T07:07:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681750</loc>
  <lastmod>2026-04-21T07:07:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的システムの分類：モデルベースとサポートベクターマシン（Classification for Dynamical Systems: Model-based Approach and Support Vector Machines）</news:title>
   <news:publication_date>2026-04-21T07:07:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681748</loc>
  <lastmod>2026-04-21T07:07:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストの信用性評価のためのニューラルネットワークアーキテクチャ（Neural Network Architecture for Credibility Assessment of Textual Claims）</news:title>
   <news:publication_date>2026-04-21T07:07:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681746</loc>
  <lastmod>2026-04-21T06:15:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列の高次元データから因果効果を推定する手法の拡張（Estimating causal effects of time-dependent exposures on a binary endpoint in a high-dimensional setting）</news:title>
   <news:publication_date>2026-04-21T06:15:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681744</loc>
  <lastmod>2026-04-21T06:14:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程の訓練を量子アルゴリズムで高速化する（Quantum algorithms for training Gaussian Processes）</news:title>
   <news:publication_date>2026-04-21T06:14:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681742</loc>
  <lastmod>2026-04-21T06:14:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械的スピーチチェーンとワンショット話者適応（Machine Speech Chain with One-shot Speaker Adaptation）</news:title>
   <news:publication_date>2026-04-21T06:14:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681740</loc>
  <lastmod>2026-04-21T06:13:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>センサー駆動システムの信頼性を設計するフレーミングモデル（Making Sense of the World: Framing Models for Trustworthy Sensor-Driven Systems）</news:title>
   <news:publication_date>2026-04-21T06:13:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681738</loc>
  <lastmod>2026-04-21T06:13:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画のブレを「リアルに」消す技術の要点（Adversarial Spatio-Temporal Learning for Video Deblurring）</news:title>
   <news:publication_date>2026-04-21T06:13:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681736</loc>
  <lastmod>2026-04-21T06:12:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Learningが「心を読む力」に何を教えるか（What deep learning can tell us about higher cognitive functions like mindreading?）</news:title>
   <news:publication_date>2026-04-21T06:12:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681734</loc>
  <lastmod>2026-04-21T06:12:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>水中における超分子ポリマーの原子スケール高速シミュレーション（Accelerated Atomistic Simulations of a Supramolecular Polymer in Water）</news:title>
   <news:publication_date>2026-04-21T06:12:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681732</loc>
  <lastmod>2026-04-21T05:20:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像レベルラベルから学ぶ画素間意味親和性（Learning Pixel-level Semantic Affinity with Image-level Supervision for Weakly Supervised Semantic Segmentation）</news:title>
   <news:publication_date>2026-04-21T05:20:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681730</loc>
  <lastmod>2026-04-21T05:10:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Graphiteによるグラフの反復生成モデリング（Graphite: Iterative Generative Modeling of Graphs）</news:title>
   <news:publication_date>2026-04-21T05:10:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681728</loc>
  <lastmod>2026-04-21T05:10:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クッキーを越えてユーザーをつなぐ学習手法（Siamese Cookie Embedding Networks for Cross-Device User Matching）</news:title>
   <news:publication_date>2026-04-21T05:10:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681726</loc>
  <lastmod>2026-04-21T05:09:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>JPEGとJPEG2000圧縮が敵対的例（Adversarial Examples）攻撃に与える影響（The Effects of JPEG and JPEG2000 Compression on Attacks using Adversarial Examples）</news:title>
   <news:publication_date>2026-04-21T05:09:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681724</loc>
  <lastmod>2026-04-21T05:08:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BIVASによる階層的変数選択のスケーリング（BIVAS: A scalable Bayesian method for bi-level variable selection with applications）</news:title>
   <news:publication_date>2026-04-21T05:08:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681722</loc>
  <lastmod>2026-04-21T05:08:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>眼球運動シミュレーションと検出器生成による面倒なパラメータ調整の削減（Eye movement simulation and detector creation to reduce laborious parameter adjustments）</news:title>
   <news:publication_date>2026-04-21T05:08:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681720</loc>
  <lastmod>2026-04-21T05:08:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HAM10000：皮膚病変の自動診断研究を前進させた大規模皮膚画像データセット（HAM10000: A Large Collection of Multi-Source Dermatoscopic Images）</news:title>
   <news:publication_date>2026-04-21T05:08:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681718</loc>
  <lastmod>2026-04-21T04:16:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半バンディット（Semi-Bandit）フィードバックによる資源配分アルゴリズムの改良（A Better Resource Allocation Algorithm with Semi-Bandit Feedback）</news:title>
   <news:publication_date>2026-04-21T04:16:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681716</loc>
  <lastmod>2026-04-21T04:16:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3DMV：3Dマルチビュー統合による3次元意味シーン分割（3DMV: Joint 3D-Multi-View Prediction for 3D Semantic Scene Segmentation）</news:title>
   <news:publication_date>2026-04-21T04:16:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681714</loc>
  <lastmod>2026-04-21T04:16:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>唇の動きを音声から生成する研究の要点（Lip Movements Generation at a Glance）</news:title>
   <news:publication_date>2026-04-21T04:16:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681712</loc>
  <lastmod>2026-04-21T04:14:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲームアバターのシナジーと対立を埋め込みでモデル化する手法（Modeling Game Avatar Synergy and Opposition through Embedding）</news:title>
   <news:publication_date>2026-04-21T04:14:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681710</loc>
  <lastmod>2026-04-21T04:14:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化的手法で教師なし学習を制御する（Supervising Unsupervised Learning with Evolutionary Algorithm in Deep Neural Network）</news:title>
   <news:publication_date>2026-04-21T04:14:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681708</loc>
  <lastmod>2026-04-21T04:14:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短期運転意図予測に基づく自動運転判断の精度向上（Predictions of short-term driving intention using recurrent neural network on sequential data）</news:title>
   <news:publication_date>2026-04-21T04:14:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681706</loc>
  <lastmod>2026-04-21T04:13:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Actor–Criticによる抽象的要約のための訓練枠組み（Actor-Critic based Training Framework for Abstractive Summarization）</news:title>
   <news:publication_date>2026-04-21T04:13:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681704</loc>
  <lastmod>2026-04-21T03:22:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非把持操作に対する強化学習：シミュレーションから実機への移行（Reinforcement learning for non-prehensile manipulation: Transfer from simulation to physical system）</news:title>
   <news:publication_date>2026-04-21T03:22:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681702</loc>
  <lastmod>2026-04-21T03:21:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トピックモデリングに基づくマルチモーダルうつ検出（Topic Modeling Based Multi-modal Depression Detection）</news:title>
   <news:publication_date>2026-04-21T03:21:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681700</loc>
  <lastmod>2026-04-21T03:21:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組み込み向け超小型畳み込みネットワークMicronNet（MicronNet: A Highly Compact Deep Convolutional Neural Network Architecture for Real-time Embedded Traffic Sign Classification）</news:title>
   <news:publication_date>2026-04-21T03:21:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681698</loc>
  <lastmod>2026-04-21T03:21:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長文要約に挑む「Deep Communicating Agents」(Deep Communicating Agents for Abstractive Summarization)</news:title>
   <news:publication_date>2026-04-21T03:21:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681696</loc>
  <lastmod>2026-04-21T03:21:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元における平滑化オンライン凸最適化とOnline Balanced Descent（Smoothed Online Convex Optimization in High Dimensions via Online Balanced Descent）</news:title>
   <news:publication_date>2026-04-21T03:21:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681694</loc>
  <lastmod>2026-04-21T03:21:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ClickBAIT-v2によるリアルタイム物体検出の現場学習（ClickBAIT-v2: Training an Object Detector in Real-Time）</news:title>
   <news:publication_date>2026-04-21T03:21:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681692</loc>
  <lastmod>2026-04-21T03:20:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造的画像修復の進化（Structural inpainting）</news:title>
   <news:publication_date>2026-04-21T03:20:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681690</loc>
  <lastmod>2026-04-21T02:29:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習ワークフローの反復と実務（How Developers Iterate on Machine Learning Workflows）</news:title>
   <news:publication_date>2026-04-21T02:29:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681688</loc>
  <lastmod>2026-04-21T02:20:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトル埋め込み上のグラフ畳み込み：皮質表面データの学習（Graph Convolutions on Spectral Embeddings: Learning of Cortical Surface Data）</news:title>
   <news:publication_date>2026-04-21T02:20:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681686</loc>
  <lastmod>2026-04-21T02:20:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>結晶化画像の分類における深層畳み込みニューラルネットワークの適用（Classification of crystallization outcomes using deep convolutional neural networks）</news:title>
   <news:publication_date>2026-04-21T02:20:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681684</loc>
  <lastmod>2026-04-21T02:19:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応アフィニティフィールドによるセマンティックセグメンテーション（Adaptive Affinity Fields for Semantic Segmentation）</news:title>
   <news:publication_date>2026-04-21T02:19:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681682</loc>
  <lastmod>2026-04-21T02:19:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形時系列部分空間表現による行動認識（Non-Linear Temporal Subspace Representations for Activity Recognition）</news:title>
   <news:publication_date>2026-04-21T02:19:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681680</loc>
  <lastmod>2026-04-21T02:19:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共通ソースグラフを持つデータセットのカノニカル相関分析（Canonical Correlation Analysis of Datasets with a Common Source Graph）</news:title>
   <news:publication_date>2026-04-21T02:19:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681678</loc>
  <lastmod>2026-04-21T02:19:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再考：EEGベースの非侵襲的脳インタフェースの設計（Re-thinking EEG-based non-invasive brain interfaces: modeling and analysis）</news:title>
   <news:publication_date>2026-04-21T02:19:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681676</loc>
  <lastmod>2026-04-21T01:27:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子構造計算のための量子機械学習（Quantum Machine Learning for Electronic Structure Calculations）</news:title>
   <news:publication_date>2026-04-21T01:27:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681674</loc>
  <lastmod>2026-04-21T01:25:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトルから銀河の物理量を推定する機械学習手法の進化（GAME: GAlaxy Machine learning for Emission lines）</news:title>
   <news:publication_date>2026-04-21T01:25:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681672</loc>
  <lastmod>2026-04-21T01:18:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネルリッジ回帰におけるクラスタリングと階層行列形式の研究（A Study of Clustering Techniques and Hierarchical Matrix Formats for Kernel Ridge Regression）</news:title>
   <news:publication_date>2026-04-21T01:18:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681670</loc>
  <lastmod>2026-04-21T01:17:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライバシー保護された予測（Privacy-preserving Prediction）</news:title>
   <news:publication_date>2026-04-21T01:17:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681668</loc>
  <lastmod>2026-04-21T01:16:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CANDELSにおける多波長バルジ・ディスク分解カタログ（A catalog of polychromatic bulge-disk decompositions of ~17.600 galaxies in CANDELS）</news:title>
   <news:publication_date>2026-04-21T01:16:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681666</loc>
  <lastmod>2026-04-21T01:16:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>疾患軌跡を読むための深層学習アプローチ（Disease-Atlas: Navigating Disease Trajectories using Deep Learning）</news:title>
   <news:publication_date>2026-04-21T01:16:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681664</loc>
  <lastmod>2026-04-21T01:15:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い優先度衝突のゼロオーバーヘッドな曖昧性除去（Towards Zero-Overhead Disambiguation of Deep Priority Conflicts）</news:title>
   <news:publication_date>2026-04-21T01:15:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681654</loc>
  <lastmod>2026-04-21T00:23:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個人間の相互作用予測（Predicting interactions between individuals with structural and dynamical information）</news:title>
   <news:publication_date>2026-04-21T00:23:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681652</loc>
  <lastmod>2026-04-21T00:17:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HDM-Netによる単眼非剛体3D再構成の新展開（HDM-Net: Monocular Non-Rigid 3D Reconstruction with Learned Deformation Model）</news:title>
   <news:publication_date>2026-04-21T00:17:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681650</loc>
  <lastmod>2026-04-21T00:15:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一分子ナノポア検出のための畳み込みニューラルネットワークQuipuNet（QuipuNet: convolutional neural network for single-molecule nanopore sensing）</news:title>
   <news:publication_date>2026-04-21T00:15:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681648</loc>
  <lastmod>2026-04-21T00:15:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネル行列近似のための分散適応サンプリング（Distributed Adaptive Sampling for Kernel Matrix Approximation）</news:title>
   <news:publication_date>2026-04-21T00:15:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681646</loc>
  <lastmod>2026-04-21T00:15:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stein Pointsによる代表点列による事後近似の効率化（Stein Points）</news:title>
   <news:publication_date>2026-04-21T00:15:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681644</loc>
  <lastmod>2026-04-21T00:13:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周囲カメラとルートプランナーを用いた運転モデルのエンドツーエンド学習 (End-to-End Learning of Driving Models with Surround-View Cameras and Route Planners)</news:title>
   <news:publication_date>2026-04-21T00:13:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681642</loc>
  <lastmod>2026-04-21T00:13:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次拡張による畳み込みニューラルネットワークの学習効率化（Incremental Training of Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-04-21T00:13:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681640</loc>
  <lastmod>2026-04-20T23:21:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安全なエンドツーエンド模倣学習によるモデル予測制御（Safe end-to-end imitation learning for model predictive control）</news:title>
   <news:publication_date>2026-04-20T23:21:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681638</loc>
  <lastmod>2026-04-20T23:21:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習による分岐（Learning to Branch）</news:title>
   <news:publication_date>2026-04-20T23:21:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681636</loc>
  <lastmod>2026-04-20T23:21:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話者適応の実証評価（Empirical Evaluation of Speaker Adaptation on DNN based Acoustic Model）</news:title>
   <news:publication_date>2026-04-20T23:21:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681634</loc>
  <lastmod>2026-04-20T23:20:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>あなたはメタデータ：ソーシャルメディア利用者の識別と難読化（You Are Your Metadata: Identification and Obfuscation of Social Media Users using Metadata Information）</news:title>
   <news:publication_date>2026-04-20T23:20:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681632</loc>
  <lastmod>2026-04-20T23:20:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク境界を前提としない継続学習の実装（Task Agnostic Continual Learning Using Online Variational Bayes）</news:title>
   <news:publication_date>2026-04-20T23:20:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681630</loc>
  <lastmod>2026-04-20T23:19:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声の残響除去におけるGANの活用（Investigating Generative Adversarial Networks based Speech Dereverberation for Robust Speech Recognition）</news:title>
   <news:publication_date>2026-04-20T23:19:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681628</loc>
  <lastmod>2026-04-20T23:19:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベンガル語の実数読み上げ音声コーパスの構築（Comprehending Real Numbers: Development of Bengali Real Number Speech Corpus）</news:title>
   <news:publication_date>2026-04-20T23:19:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681626</loc>
  <lastmod>2026-04-20T22:28:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライバシー保護型機械学習の脅威と解決策（Privacy Preserving Machine Learning: Threats and Solutions）</news:title>
   <news:publication_date>2026-04-20T22:28:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681624</loc>
  <lastmod>2026-04-20T22:27:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>世界モデルの構築と活用（World Models）</news:title>
   <news:publication_date>2026-04-20T22:27:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681622</loc>
  <lastmod>2026-04-20T22:26:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期的形状変化分布の学習：微分同相写像の多様体上の階層モデル（Learning distributions of shape trajectories from longitudinal datasets: a hierarchical model on a manifold of diffeomorphisms）</news:title>
   <news:publication_date>2026-04-20T22:26:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681620</loc>
  <lastmod>2026-04-20T22:26:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepScores：小さな物体の検出・分類のための大規模楽譜データセット（DeepScores – A Dataset for Segmentation, Detection and Classification of Tiny Objects）</news:title>
   <news:publication_date>2026-04-20T22:26:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681618</loc>
  <lastmod>2026-04-20T22:26:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡張演算子による点群畳み込み（Point Convolutional Neural Networks by Extension Operators）</news:title>
   <news:publication_date>2026-04-20T22:26:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681616</loc>
  <lastmod>2026-04-20T22:25:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CHiME-4を使った雑音下音声認識の単一ベースライン構築（Building state-of-the-art distant speech recognition using the CHiME-4 challenge with a setup of speech enhancement baseline）</news:title>
   <news:publication_date>2026-04-20T22:25:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681614</loc>
  <lastmod>2026-04-20T22:25:04Z</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DNAハイブリダイゼーション解析（Analyzing DNA Hybridization via machine learning）</news:title>
   <news:publication_date>2026-04-20T22:25:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681612</loc>
  <lastmod>2026-04-20T21:33:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な多領域ディープニューラルネットワークの表現（Efficient parametrization of multi-domain deep neural networks）</news:title>
   <news:publication_date>2026-04-20T21:33:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681610</loc>
  <lastmod>2026-04-20T21:33:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepJDOTによる深層結合分布の最適輸送で実現する教師なしドメイン適応（DeepJDOT: Deep Joint Distribution Optimal Transport for Unsupervised Domain Adaptation）</news:title>
   <news:publication_date>2026-04-20T21:33:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681608</loc>
  <lastmod>2026-04-20T21:33:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク理論と機械学習を用いたエルニーニョ予測（Using network theory and machine learning to predict El Niño）</news:title>
   <news:publication_date>2026-04-20T21:33:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681606</loc>
  <lastmod>2026-04-20T21:31:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的PETのキネティック圧縮センシング（Kinetic Compressive Sensing）</news:title>
   <news:publication_date>2026-04-20T21:31:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681604</loc>
  <lastmod>2026-04-20T21:31:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソルグラフ畳み込みニューラルネットワークの要点と経営への示唆（Tensor graph convolutional neural network）</news:title>
   <news:publication_date>2026-04-20T21:31:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681602</loc>
  <lastmod>2026-04-20T21:31:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>6自由度オブジェクトトラッキングの評価フレームワーク (A Framework for Evaluating 6-DOF Object Trackers)</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681600</loc>
  <lastmod>2026-04-20T21:31:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>活性メモリによる高速パラメトリック学習（Fast Parametric Learning with Activation Memorization）</news:title>
   <news:publication_date>2026-04-20T21:31:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681598</loc>
  <lastmod>2026-04-20T20:38:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの深度学習と焦点距離の埋め込み（Learning Depth from Single Images with Deep Neural Network Embedding Focal Length）</news:title>
   <news:publication_date>2026-04-20T20:38:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681596</loc>
  <lastmod>2026-04-20T20:38:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Return of the features — 効率的な特徴選択と解釈性の高いフォトメトリック赤方偏移推定（Efficient feature selection and interpretation for photometric redshifts）</news:title>
   <news:publication_date>2026-04-20T20:38:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681594</loc>
  <lastmod>2026-04-20T20:37:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンゴテクスチャ画像の高精度分類を目指して（Towards Highly Accurate Coral Texture Images Classification Using Deep Convolutional Neural Networks and Data Augmentation）</news:title>
   <news:publication_date>2026-04-20T20:37:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681592</loc>
  <lastmod>2026-04-20T20:36:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BLSTMマスクを使った単一チャネル音声強調の学生–教師学習（Student-Teacher Learning for BLSTM Mask-based Speech Enhancement）</news:title>
   <news:publication_date>2026-04-20T20:36:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681590</loc>
  <lastmod>2026-04-20T20:36:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イベント時刻だけからネットワーク接続を推定する理論（Inferring network connectivity from event timing patterns）</news:title>
   <news:publication_date>2026-04-20T20:36:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681588</loc>
  <lastmod>2026-04-20T20:36:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元空間における交差検証の効率化（Cross-validation in high-dimensional spaces: a lifeline for least-squares models and multi-class LDA）</news:title>
   <news:publication_date>2026-04-20T20:36:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681586</loc>
  <lastmod>2026-04-20T20:36:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群衆に紛れるプライベート平均化の実現（Hiding in the Crowd: A Massively Distributed Algorithm for Private Averaging with Malicious Adversaries）</news:title>
   <news:publication_date>2026-04-20T20:36:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681584</loc>
  <lastmod>2026-04-20T19:44:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習を用いた公平な動的価格設定（Reinforcement Learning for Fair Dynamic Pricing）</news:title>
   <news:publication_date>2026-04-20T19:44:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681582</loc>
  <lastmod>2026-04-20T19:44:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>押しと掴みの協調を自己監督で学ぶ（Learning Synergies between Pushing and Grasping with Self-supervised Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-20T19:44:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681580</loc>
  <lastmod>2026-04-20T19:43:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い非弾性散乱におけるジェット生成のN3LO補正（N3LO Corrections to Jet Production in Deep Inelastic Scattering using the Projection-to-Born Method）</news:title>
   <news:publication_date>2026-04-20T19:43:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681578</loc>
  <lastmod>2026-04-20T19:43:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重力波検出器における雑音トランジェントの画像ベース深層学習による分類（Image-based deep learning for classification of noise transients in gravitational wave detectors）</news:title>
   <news:publication_date>2026-04-20T19:43:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681576</loc>
  <lastmod>2026-04-20T19:42:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈を考慮した特徴列のための二重注意マッチングネットワーク (Dual Attention Matching Network for Context-Aware Feature Sequence based Person Re-Identification)</news:title>
   <news:publication_date>2026-04-20T19:42:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681574</loc>
  <lastmod>2026-04-20T19:42:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複素数値Restricted Boltzmann Machineによる複素スペクトルからの直接音声パラメータ化（Complex-Valued Restricted Boltzmann Machine for Direct Speech Parameterization from Complex Spectra）</news:title>
   <news:publication_date>2026-04-20T19:42:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681572</loc>
  <lastmod>2026-04-20T19:42:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>指向変調による5G以降のセキュア通信（Directional Modulation: A Secure Solution to 5G and Beyond Mobile Networks）</news:title>
   <news:publication_date>2026-04-20T19:42:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681570</loc>
  <lastmod>2026-04-20T18:51:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Diagonalwise RefactorizationによるDepthwise Convolutionの高速学習（Diagonalwise Refactorization: An Efficient Training Method for Depthwise Convolutions）</news:title>
   <news:publication_date>2026-04-20T18:51:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681568</loc>
  <lastmod>2026-04-20T18:50:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>匿名化されたマルチエージェント環境におけるエントロピー基準の独立学習（Entropy Based Independent Learning in Anonymous Multi-Agent Settings）</news:title>
   <news:publication_date>2026-04-20T18:50:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681566</loc>
  <lastmod>2026-04-20T18:50:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手作り特徴と深層姿勢ベース領域特徴の融合による人物再識別（Person re-identification with fusion of hand-crafted and deep pose-based body region features）</news:title>
   <news:publication_date>2026-04-20T18:50:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681564</loc>
  <lastmod>2026-04-20T18:50:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>微分可能プログラミングの解剖（Demystifying Differentiable Programming: Shift/Reset the Penultimate Backpropagator）</news:title>
   <news:publication_date>2026-04-20T18:50:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681562</loc>
  <lastmod>2026-04-20T18:49:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数判別器を用いたCycleGANによる非並列音声ドメイン適応（A Multi-Discriminator CycleGAN for Unsupervised Non-Parallel Speech Domain Adaptation）</news:title>
   <news:publication_date>2026-04-20T18:49:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681560</loc>
  <lastmod>2026-04-20T18:49:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mittens：既存語彙表現を領域特化させる手法（Mittens: An Extension of GloVe for Learning Domain-Specialized Representations）</news:title>
   <news:publication_date>2026-04-20T18:49:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681558</loc>
  <lastmod>2026-04-20T18:49:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケール構造認識ネットワークによる姿勢推定（Multi-Scale Structure-Aware Network for Human Pose Estimation）</news:title>
   <news:publication_date>2026-04-20T18:49:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681556</loc>
  <lastmod>2026-04-20T17:58:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>目標から逆算して学ぶ強化学習（Forward-Backward Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-20T17:58:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681554</loc>
  <lastmod>2026-04-20T17:58:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MLE誘導尤度によるマルコフ確率場の近似 (MLE-induced Likelihood for Markov Random Fields)</news:title>
   <news:publication_date>2026-04-20T17:58:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681552</loc>
  <lastmod>2026-04-20T17:57:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CISE分散研究インフラの未来（The Future of CISE Distributed Research Infrastructure）</news:title>
   <news:publication_date>2026-04-20T17:57:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681550</loc>
  <lastmod>2026-04-20T17:57:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitter API制限を回避するウェブスクレイピング手法（A Web Scraping Methodology for Bypassing Twitter API Restrictions）</news:title>
   <news:publication_date>2026-04-20T17:57:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681548</loc>
  <lastmod>2026-04-20T17:56:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画ベース人物再識別のための多様性正則化時空間注意（Diversity Regularized Spatiotemporal Attention for Video-based Person Re-identification）</news:title>
   <news:publication_date>2026-04-20T17:56:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681546</loc>
  <lastmod>2026-04-20T17:56:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CompNetによる脳MRIの抽出精度向上（CompNet: Complementary Segmentation Network for Brain MRI Extraction）</news:title>
   <news:publication_date>2026-04-20T17:56:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681544</loc>
  <lastmod>2026-04-20T17:56:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DRACO：冗長勾配によるビザンチン耐性分散学習（Byzantine-resilient Distributed Training via Redundant Gradients）</news:title>
   <news:publication_date>2026-04-20T17:56:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681542</loc>
  <lastmod>2026-04-20T17:04:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Feature Squeezingの検出をすり抜ける攻撃強化の問題（BYPASSING FEATURE SQUEEZING BY INCREASING ADVERSARY STRENGTH）</news:title>
   <news:publication_date>2026-04-20T17:04:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681540</loc>
  <lastmod>2026-04-20T17:04:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己教師的サンプルマイニングによる人間機械協調の促進（Towards Human-Machine Cooperation: Self-supervised Sample Mining for Object Detection）</news:title>
   <news:publication_date>2026-04-20T17:04:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681538</loc>
  <lastmod>2026-04-20T17:03:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UCT木探索によるエンパワーメント計算の高速化（Accelerating Empowerment Computation with UCT Tree Search）</news:title>
   <news:publication_date>2026-04-20T17:03:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681536</loc>
  <lastmod>2026-04-20T17:02:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>てんかん発作検出の深層学習アプローチ（Epileptic Seizure Detection: A Deep Learning Approach）</news:title>
   <news:publication_date>2026-04-20T17:02:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681534</loc>
  <lastmod>2026-04-20T17:02:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>属性を作用素として扱う：未知の属性-物体組合せの分解 (Attributes as Operators: Factorizing Unseen Attribute-Object Compositions)</news:title>
   <news:publication_date>2026-04-20T17:02:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681532</loc>
  <lastmod>2026-04-20T17:01:50Z</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>2026-04-20T17:01:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-20T17:01:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Webから学ぶセマンティックセグメンテーション（WebSeg: Learning Semantic Segmentation from Web Searches）</news:title>
   <news:publication_date>2026-04-20T17:01:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681528</loc>
  <lastmod>2026-04-20T16:09:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リンクド・オープンデータにおける基礎的区別の実証的分析（Empirical Analysis of Foundational Distinctions in Linked Open Data）</news:title>
   <news:publication_date>2026-04-20T16:09:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681526</loc>
  <lastmod>2026-04-20T16:09:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習によるメタ安定多形の振動特性予測（Vibrational properties of metastable polymorph structures by machine learning）</news:title>
   <news:publication_date>2026-04-20T16:09:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681524</loc>
  <lastmod>2026-04-20T16:08:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ない注釈データで地表画像をピクセル単位で識別する方法（Low-Shot Learning for the Semantic Segmentation of Remote Sensing Imagery）</news:title>
   <news:publication_date>2026-04-20T16:08:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681522</loc>
  <lastmod>2026-04-20T16:08:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>雪上の女性も写すキャプション生成の偏りを正す研究（Women also Snowboard: Overcoming Bias in Captioning Models）</news:title>
   <news:publication_date>2026-04-20T16:08:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681520</loc>
  <lastmod>2026-04-20T16:08:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークのハイパーパラメータに対する規律あるアプローチ（A Disciplined Approach to Neural Network Hyper-Parameters: Part 1 – Learning Rate, Batch Size, Momentum, and Weight Decay）</news:title>
   <news:publication_date>2026-04-20T16:08:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681518</loc>
  <lastmod>2026-04-20T16:07:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声強調における模倣損失の導入（SPECTRAL FEATURE MAPPING WITH MIMIC LOSS FOR ROBUST SPEECH RECOGNITION）</news:title>
   <news:publication_date>2026-04-20T16:07:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681516</loc>
  <lastmod>2026-04-20T16:07:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルデータ解析のための深層学習（Deep learning as a tool for neural data analysis: speech classification and cross-frequency coupling in human sensorimotor cortex）</news:title>
   <news:publication_date>2026-04-20T16:07:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681514</loc>
  <lastmod>2026-04-20T15:15:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>識別的プーリングによる動画表現学習 (Video Representation Learning Using Discriminative Pooling)</news:title>
   <news:publication_date>2026-04-20T15:15:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681512</loc>
  <lastmod>2026-04-20T15:07:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的環境でゴール指向の自律性を示すチャットボット（On Chatbots Exhibiting Goal-Directed Autonomy in Dynamic Environments）</news:title>
   <news:publication_date>2026-04-20T15:07:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681510</loc>
  <lastmod>2026-04-20T15:07:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然勾配とテイラー近似を結ぶ共通枠組み（A Common Framework for Natural Gradient and Taylor based Optimisation using Manifold Theory）</news:title>
   <news:publication_date>2026-04-20T15:07:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681508</loc>
  <lastmod>2026-04-20T15:06:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移可能な属性・識別共同深層学習による教師なし人物再識別（Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification）</news:title>
   <news:publication_date>2026-04-20T15:06:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681506</loc>
  <lastmod>2026-04-20T15:06:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>膨張黒鉛に埋め込まれたタンタル標的のスケール試作と陽子ビーム衝撃下の評価（Scaled prototype of a tantalum target embedded in expanded graphite for antiproton production）</news:title>
   <news:publication_date>2026-04-20T15:06:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681504</loc>
  <lastmod>2026-04-20T15:05:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習アーキテクチャにおける量子もつれの表現力（Quantum Entanglement in Deep Learning Architectures）</news:title>
   <news:publication_date>2026-04-20T15:05:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681502</loc>
  <lastmod>2026-04-20T15:04:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短時間実行で不良設定を素早く打ち切るための方策学習（Algorithm Configuration: Learning policies for the quick termination of poor performers）</news:title>
   <news:publication_date>2026-04-20T15:04:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681500</loc>
  <lastmod>2026-04-20T14:13:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>JWSTに向けた高赤方偏移のUV光度関数予測（Semi-analytic forecasts for JWST - I. UV luminosity functions at z = 4 - 10）</news:title>
   <news:publication_date>2026-04-20T14:13:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681498</loc>
  <lastmod>2026-04-20T14:13:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変換的状態による未来予測（Predicting the Future with Transformational States）</news:title>
   <news:publication_date>2026-04-20T14:13:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681496</loc>
  <lastmod>2026-04-20T14:12:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別最適化モデルを分散で学ぶ方法—DJAM（DJAM: distributed Jacobi asynchronous method for learning personal models）</news:title>
   <news:publication_date>2026-04-20T14:12:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681494</loc>
  <lastmod>2026-04-20T14:11:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>移動ロボットによる回復性のある能動的情報収集（Resilient Active Information Gathering with Mobile Robots）</news:title>
   <news:publication_date>2026-04-20T14:11:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681492</loc>
  <lastmod>2026-04-20T14:11:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期宇宙における暗黒物質–バリオン散乱の制約と21cm信号への示唆（Early‑Universe Constraints on Dark Matter-Baryon Scattering and their Implications for a Global 21cm Signal）</news:title>
   <news:publication_date>2026-04-20T14:11:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681490</loc>
  <lastmod>2026-04-20T14:11:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン転移に強い属性埋め込みを用いた識別モデル（Domain transfer convolutional attribute embedding）</news:title>
   <news:publication_date>2026-04-20T14:11:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681488</loc>
  <lastmod>2026-04-20T14:10:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声認識に特化した軽量GRU設計：Light GRU（Light Gated Recurrent Units for Speech Recognition）</news:title>
   <news:publication_date>2026-04-20T14:10:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681486</loc>
  <lastmod>2026-04-20T13:19:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>野外での3D人体姿勢推定を敵対的学習で実現する（3D Human Pose Estimation in the Wild by Adversarial Learning）</news:title>
   <news:publication_date>2026-04-20T13:19:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681484</loc>
  <lastmod>2026-04-20T13:18:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stereoによる高精度深度推定の重要性と効率的半教師あり学習（On the Importance of Stereo for Accurate Depth Estimation: An Efficient Semi-Supervised Deep Neural Network Approach）</news:title>
   <news:publication_date>2026-04-20T13:18:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681482</loc>
  <lastmod>2026-04-20T13:17:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Polygon-RNN++による効率的なポリゴン注釈（Efficient Interactive Annotation of Segmentation Datasets with Polygon-RNN++）</news:title>
   <news:publication_date>2026-04-20T13:17:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681480</loc>
  <lastmod>2026-04-20T13:17:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列予測における記憶ベースの序数回帰深層ニューラルネットワーク（MOrdReD: Memory-based Ordinal Regression Deep Neural Networks for Time Series Forecasting）</news:title>
   <news:publication_date>2026-04-20T13:17:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681478</loc>
  <lastmod>2026-04-20T13:16:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動きから読み解くフロー：ウェアラブルと深層学習による最適パフォーマンス検出（Flow From Motion: A Deep Learning Approach）</news:title>
   <news:publication_date>2026-04-20T13:16:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681476</loc>
  <lastmod>2026-04-20T13:16:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人と機械が共に学ぶHAMLET：説明可能なラベリング改善手法（HAMLET: Interpretable Human And Machine co-LEarning Technique）</news:title>
   <news:publication_date>2026-04-20T13:16:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681474</loc>
  <lastmod>2026-04-20T13:16:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カメラ画像と機械学習で先読みする受信電力予測（Proactive Received Power Prediction Using Machine Learning and Depth Images for mmWave Networks）</news:title>
   <news:publication_date>2026-04-20T13:16:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681472</loc>
  <lastmod>2026-04-20T12:24:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BAGANによる不均衡データのためのデータ拡張（BAGAN: Data Augmentation with Balancing GAN）</news:title>
   <news:publication_date>2026-04-20T12:24:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681470</loc>
  <lastmod>2026-04-20T12:24:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像表現の内在次元（On the Intrinsic Dimensionality of Image Representations）</news:title>
   <news:publication_date>2026-04-20T12:24:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681468</loc>
  <lastmod>2026-04-20T12:23:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光の偏光を芸術と結びつけて教える教育実践（Teaching Light Polarization by Putting Art and Physics Together）</news:title>
   <news:publication_date>2026-04-20T12:23:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681466</loc>
  <lastmod>2026-04-20T12:23:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数巡回セールスマン問題を学習する順序不変プーリングネットワーク（Learning the Multiple Traveling Salesmen Problem with Permutation Invariant Pooling Networks）</news:title>
   <news:publication_date>2026-04-20T12:23:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681464</loc>
  <lastmod>2026-04-20T12:23:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的例の部分空間を特徴づける局所内在次元の限界（ON THE LIMITATION OF LOCAL INTRINSIC DIMENSIONALITY FOR CHARACTERIZING THE SUBSPACES OF ADVERSARIAL EXAMPLES）</news:title>
   <news:publication_date>2026-04-20T12:23:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681462</loc>
  <lastmod>2026-04-20T12:22:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生体信号の類似性に基づく階層的クラスタリングで健康状態を識別する（Similarity based hierarchical clustering of physiological parameters for the identification of health states – a feasibility study）</news:title>
   <news:publication_date>2026-04-20T12:22:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681460</loc>
  <lastmod>2026-04-20T12:22:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的に生成されるペアワイズ制約による距離学習が耳認識にもたらす変化（Metric Learning with Dynamically Generated Pairwise Constraints for Ear Recognition）</news:title>
   <news:publication_date>2026-04-20T12:22:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681458</loc>
  <lastmod>2026-04-20T11:30:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像データセットの分類難易度を高速推定する方法（Efficient Image Dataset Classification Difficulty Estimation for Predicting Deep-Learning Accuracy）</news:title>
   <news:publication_date>2026-04-20T11:30:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681456</loc>
  <lastmod>2026-04-20T11:30:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セッションベース推薦アルゴリズムの評価（Evaluation of Session-based Recommendation Algorithms）</news:title>
   <news:publication_date>2026-04-20T11:30:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681454</loc>
  <lastmod>2026-04-20T11:29:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一スコア比較では機械学習手法の優劣は決められない（Why Comparing Single Performance Scores Does Not Allow to Draw Conclusions About Machine Learning Approaches）</news:title>
   <news:publication_date>2026-04-20T11:29:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681452</loc>
  <lastmod>2026-04-20T11:28:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プログラム性質予測のための一般的なパスベース表現（A General Path-Based Representation for Predicting Program Properties）</news:title>
   <news:publication_date>2026-04-20T11:28:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681450</loc>
  <lastmod>2026-04-20T11:28:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トピックとソーシャル潜在因子を組み込んだ協調フィルタリング（Collaborative Filtering with Topic and Social Latent Factors Incorporating Implicit Feedback）</news:title>
   <news:publication_date>2026-04-20T11:28:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681448</loc>
  <lastmod>2026-04-20T11:28:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼できる予測区間を作る方法（Calibrated Prediction Intervals for Neural Network Regressors）</news:title>
   <news:publication_date>2026-04-20T11:28:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681446</loc>
  <lastmod>2026-04-20T11:27:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイキングニューラルネットワークにおける長期短期記憶と学習の学習（Long short-term memory and learning-to-learn in networks of spiking neurons）</news:title>
   <news:publication_date>2026-04-20T11:27:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681444</loc>
  <lastmod>2026-04-20T10:35:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マッチングパースートと座標降下の統一的解析（On Matching Pursuit and Coordinate Descent）</news:title>
   <news:publication_date>2026-04-20T10:35:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681442</loc>
  <lastmod>2026-04-20T10:35:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学生履修履歴から学ぶ接続主義的レコメンデーション（Connectionist Recommendation in the Wild: On the utility and scrutability of neural networks for personalized course guidance）</news:title>
   <news:publication_date>2026-04-20T10:35:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681440</loc>
  <lastmod>2026-04-20T10:34:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子生成モデルの評価指標としてのFréchet ChemNet Distance（Fréchet ChemNet Distance: A metric for generative models for molecules in drug discovery）</news:title>
   <news:publication_date>2026-04-20T10:34:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681438</loc>
  <lastmod>2026-04-20T10:33:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>患者来院データの深層表現化（Deep Representation for Patient Visits from Electronic Health Records）</news:title>
   <news:publication_date>2026-04-20T10:33:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681436</loc>
  <lastmod>2026-04-20T10:33:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習に対する理論的に正しい訓練アルゴリズムの実装可能性（A Provably Correct Algorithm for Deep Learning that Actually Works）</news:title>
   <news:publication_date>2026-04-20T10:33:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681434</loc>
  <lastmod>2026-04-20T10:33:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己注意に基づく音響モデル（Self-Attentional Acoustic Models）</news:title>
   <news:publication_date>2026-04-20T10:33:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681432</loc>
  <lastmod>2026-04-20T10:32:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>株式のクラスタ分析と高頻度データの活用（Cluster analysis of stocks using price movements of high frequency data from National Stock Exchange）</news:title>
   <news:publication_date>2026-04-20T10:32:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681430</loc>
  <lastmod>2026-04-20T09:41:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoT大量機器向けAloha-NOMAによる非同期ランダムアクセスの提案（Enabling Aloha-NOMA for Massive M2M Communication in IoT Networks）</news:title>
   <news:publication_date>2026-04-20T09:41:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681428</loc>
  <lastmod>2026-04-20T09:41:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インフレーションの決定的な未来（The decisive future of inflation）</news:title>
   <news:publication_date>2026-04-20T09:41:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681426</loc>
  <lastmod>2026-04-20T09:41:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑な活動の無教師分割（Unsupervised Learning and Segmentation of Complex Activities from Video）</news:title>
   <news:publication_date>2026-04-20T09:41:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681424</loc>
  <lastmod>2026-04-20T09:39:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コードをベクトルで表す思想と実践（code2vec: Learning Distributed Representations of Code）</news:title>
   <news:publication_date>2026-04-20T09:39:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681422</loc>
  <lastmod>2026-04-20T09:39:34Z</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・シースルー光場レンダリング（Semantic See-Through Rendering on Light Fields）</news:title>
   <news:publication_date>2026-04-20T09:39:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681420</loc>
  <lastmod>2026-04-20T09:39:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>界面再結合と注入障壁がペロブスカイト太陽電池の電気特性に与える影響（The effects of interfacial recombination and injection barrier on the electrical characteristics of perovskite solar cells）</news:title>
   <news:publication_date>2026-04-20T09:39:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681418</loc>
  <lastmod>2026-04-20T09:38:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交差ランダム効果モデルのスケーラブル推論（Scalable inference for crossed random effects models）</news:title>
   <news:publication_date>2026-04-20T09:38:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681416</loc>
  <lastmod>2026-04-20T08:46:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報蒸留ネットワークによる高速・高精度単一画像超解像（Fast and Accurate Single Image Super-Resolution via Information Distillation Network）</news:title>
   <news:publication_date>2026-04-20T08:46:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681414</loc>
  <lastmod>2026-04-20T08:46:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>センサーパターンノイズと深層学習によるCG判別（Distinguishing Computer-generated Graphics from Natural Images Based on Sensor Pattern Noise and Deep Learning）</news:title>
   <news:publication_date>2026-04-20T08:46:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681412</loc>
  <lastmod>2026-04-20T08:46:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時分割多重化によるスケーラブルな光フォトニック強化学習（Scalable photonic reinforcement learning by time-division multiplexing of laser chaos）</news:title>
   <news:publication_date>2026-04-20T08:46:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681410</loc>
  <lastmod>2026-04-20T08:45:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成敵対ネットワークを用いたマルチサイト脳画像の差異補正（Correcting differences in multi-site neuroimaging data using Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-04-20T08:45:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681408</loc>
  <lastmod>2026-04-20T08:45:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自律走行における深層学習アーキテクチャの体系的比較（A Systematic Comparison of Deep Learning Architectures in an Autonomous Vehicle）</news:title>
   <news:publication_date>2026-04-20T08:45:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681406</loc>
  <lastmod>2026-04-20T08:45:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン二次法による非凸確率的最適化（Online Second Order Methods for Non-Convex Stochastic Optimizations）</news:title>
   <news:publication_date>2026-04-20T08:45:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681404</loc>
  <lastmod>2026-04-20T08:45:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚質問応答における一般化ハダマード積融合演算子（Generalized Hadamard-Product Fusion Operators for Visual Question Answering）</news:title>
   <news:publication_date>2026-04-20T08:45:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681402</loc>
  <lastmod>2026-04-20T07:53:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不適切学習が切り拓くオンラインロジスティック回帰の新展開（Logistic Regression: The Importance of Being Improper）</news:title>
   <news:publication_date>2026-04-20T07:53:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681400</loc>
  <lastmod>2026-04-20T07:44:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔認証におけるパッチ特徴とソフト顔属性を組み合わせた署名（A Face Recognition Signature Combining Patch-based Features with Soft Facial Attributes）</news:title>
   <news:publication_date>2026-04-20T07:44:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681398</loc>
  <lastmod>2026-04-20T07:44:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経験的リスクの局所最小値について（On the Local Minima of the Empirical Risk）</news:title>
   <news:publication_date>2026-04-20T07:44:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681396</loc>
  <lastmod>2026-04-20T07:43:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的汚染に強い確率的バンディット（Stochastic bandits robust to adversarial corruptions）</news:title>
   <news:publication_date>2026-04-20T07:43:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681394</loc>
  <lastmod>2026-04-20T07:43:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>状態変換と損失変換で見るニューラルネットの構造（Neural Nets via Forward State Transformation and Backward Loss Transformation）</news:title>
   <news:publication_date>2026-04-20T07:43:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681392</loc>
  <lastmod>2026-04-20T07:43:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepVesselNet：3次元血管画像から血管構造を効率的に抽出する手法（DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumes）</news:title>
   <news:publication_date>2026-04-20T07:43:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681390</loc>
  <lastmod>2026-04-20T07:42:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓MRI画像の学習ベース品質管理（Learning-Based Quality Control for Cardiac MR Images）</news:title>
   <news:publication_date>2026-04-20T07:42:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681388</loc>
  <lastmod>2026-04-20T06:51:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークの勾配安定化を実現するSVDパラメータ化（Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization）</news:title>
   <news:publication_date>2026-04-20T06:51:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681386</loc>
  <lastmod>2026-04-20T06:51:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師あり学習としてのテキスト分割（Text Segmentation as a Supervised Learning Task）</news:title>
   <news:publication_date>2026-04-20T06:51:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681384</loc>
  <lastmod>2026-04-20T06:51:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一RGB-D画像の深度補完（Deep Depth Completion of a Single RGB-D Image）</news:title>
   <news:publication_date>2026-04-20T06:51:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681382</loc>
  <lastmod>2026-04-20T06:50:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>仕様のあいまいさを「見える化」するスケルトン合成（Synthesizing Skeletons for Reactive Systems）</news:title>
   <news:publication_date>2026-04-20T06:50:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681380</loc>
  <lastmod>2026-04-20T06:50:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SUNLayerによる安定的な復元：生成ネットワークでのデノイズ理論（SUNLayer: Stable denoising with generative networks）</news:title>
   <news:publication_date>2026-04-20T06:50:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681378</loc>
  <lastmod>2026-04-20T06:50:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルエッジコンピューティングの性能最適化（Performance Optimization in Mobile-Edge Computing via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-20T06:50:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681376</loc>
  <lastmod>2026-04-20T06:49:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型クロージャーの発見（Data-driven Discovery of Closure Models）</news:title>
   <news:publication_date>2026-04-20T06:49:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681374</loc>
  <lastmod>2026-04-20T05:58:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群変換の双方向学習ネットワーク（P2P-NET: Bidirectional Point Displacement Net for Shape Transform）</news:title>
   <news:publication_date>2026-04-20T05:58:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681372</loc>
  <lastmod>2026-04-20T05:58:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小さい頭部検出を精緻化する手法の実務的解説（Detecting Heads using Feature Refine Net and Cascaded Multi-scale Architecture）</news:title>
   <news:publication_date>2026-04-20T05:58:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681370</loc>
  <lastmod>2026-04-20T05:58:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>COSMOS領域におけるDEIMOS 10K分光サーベイカタログ（The DEIMOS 10K Spectroscopic Survey Catalog of the COSMOS Field）</news:title>
   <news:publication_date>2026-04-20T05:58:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681368</loc>
  <lastmod>2026-04-20T05:57:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフのベルヌーイ埋め込み（Bernoulli Embeddings for Graphs）</news:title>
   <news:publication_date>2026-04-20T05:57:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681366</loc>
  <lastmod>2026-04-20T05:57:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動車のランプ合流を強化学習で行う研究（Autonomous Ramp Merge Maneuver Based on Reinforcement Learning with Continuous Action Space）</news:title>
   <news:publication_date>2026-04-20T05:57:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681364</loc>
  <lastmod>2026-04-20T05:57:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Goldbach関数の近似に深層学習を使う（Goldbach’s Function Approximation Using Deep Learning）</news:title>
   <news:publication_date>2026-04-20T05:57:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681362</loc>
  <lastmod>2026-04-20T05:57:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチタスク学習に基づく教師なしドメイン適応（Unsupervised Domain Adaptation: A Multi-task Learning-based Method）</news:title>
   <news:publication_date>2026-04-20T05:57:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681360</loc>
  <lastmod>2026-04-20T05:06:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケール畳み込みによる環境音認識の前進（Learning Environmental Sounds with Multi-scale Convolutional Neural Network）</news:title>
   <news:publication_date>2026-04-20T05:06:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681358</loc>
  <lastmod>2026-04-20T05:06:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの教師なし深度推定と顔の3D回転・置換（Unsupervised Depth Estimation, 3D Face Rotation and Replacement）</news:title>
   <news:publication_date>2026-04-20T05:06:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681356</loc>
  <lastmod>2026-04-20T05:05:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話環境下での深層強化学習による自動運転操作（Automated Driving Maneuvers under Interactive Environment based on Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-20T05:05:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681354</loc>
  <lastmod>2026-04-20T05:04:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク履歴の回復性における相転移（Phase transition in the recoverability of network history）</news:title>
   <news:publication_date>2026-04-20T05:04:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681352</loc>
  <lastmod>2026-04-20T05:04:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>服の「相性」を学ぶ──タイプ認識埋め込みによるファッション互換性の新視点（Learning Type-Aware Embeddings for Fashion Compatibility）</news:title>
   <news:publication_date>2026-04-20T05:04:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681350</loc>
  <lastmod>2026-04-20T05:04:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知システムの出力フィードバック制御に関する有限データ性能保証（Finite-Data Performance Guarantees for the Output-Feedback Control of an Unknown System）</news:title>
   <news:publication_date>2026-04-20T05:04:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681348</loc>
  <lastmod>2026-04-20T05:03:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーングラフ解析を依存構文解析として扱う手法（Scene Graph Parsing as Dependency Parsing）</news:title>
   <news:publication_date>2026-04-20T05:03:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681346</loc>
  <lastmod>2026-04-20T04:11:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シミュレーションから現実世界への教師なしドメイン適応（Unsupervised Domain Adaptation: from Simulation Engine to the Real World）</news:title>
   <news:publication_date>2026-04-20T04:11:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681344</loc>
  <lastmod>2026-04-20T04:11:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡な生存データに対するバランス化ランダム生存森林（Balanced Random Survival Forests for Extremely Unbalanced, Right Censored Data）</news:title>
   <news:publication_date>2026-04-20T04:11:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681342</loc>
  <lastmod>2026-04-20T04:10:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低リソース音声からテキスト翻訳（Low-Resource Speech-to-Text Translation）</news:title>
   <news:publication_date>2026-04-20T04:10:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681340</loc>
  <lastmod>2026-04-20T04:09:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>模倣耐性プログラム挙動モデリング（Mimicry Resilient Program Behavior Modeling with LSTM based Branch Models）</news:title>
   <news:publication_date>2026-04-20T04:09:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681338</loc>
  <lastmod>2026-04-20T04:09:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類器は“安全舞台”に過ぎない — 探索的攻撃に対する脆弱性の実証（Security Theater: On the Vulnerability of Classifiers to Exploratory Attacks）</news:title>
   <news:publication_date>2026-04-20T04:09:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681336</loc>
  <lastmod>2026-04-20T04:08:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮画像に「ノイズ」を再導入して自然さを取り戻す技術（Noise generation for compression algorithms）</news:title>
   <news:publication_date>2026-04-20T04:08:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681334</loc>
  <lastmod>2026-04-20T04:08:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的敵対的マイニングによる機械学習の安全性（A Dynamic-Adversarial Mining Approach to the Security of Machine Learning）</news:title>
   <news:publication_date>2026-04-20T04:08:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681332</loc>
  <lastmod>2026-04-20T03:16:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的コンセプトドリフトへの対処法（Handling Adversarial Concept Drift in Streaming Data）</news:title>
   <news:publication_date>2026-04-20T03:16:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681330</loc>
  <lastmod>2026-04-20T03:16:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化実験で影響を受けた集団を効率的に見つける方法（Efficient Discovery of Heterogeneous Quantile Treatment Effects in Randomized Experiments via Anomalous Pattern Detection）</news:title>
   <news:publication_date>2026-04-20T03:16:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681328</loc>
  <lastmod>2026-04-20T03:16:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速な変分ベイズによる重厚尾PLDAのi-vector/x-vectorへの応用（Fast variational Bayes for heavy-tailed PLDA applied to i-vectors and x-vectors）</news:title>
   <news:publication_date>2026-04-20T03:16:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681326</loc>
  <lastmod>2026-04-20T03:15:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイク・アンド・スラブ深層学習の事後収束（Posterior Concentration for Sparse Deep Learning）</news:title>
   <news:publication_date>2026-04-20T03:15:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681324</loc>
  <lastmod>2026-04-20T03:15:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非共役変分推論における自然勾配の実践（Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models）</news:title>
   <news:publication_date>2026-04-20T03:15:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681322</loc>
  <lastmod>2026-04-20T03:15:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公共図書館におけるソーシャルメディア分析の実務的示唆（Social Media Analysis for Organizations: US Public Libraries）</news:title>
   <news:publication_date>2026-04-20T03:15:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681320</loc>
  <lastmod>2026-04-20T03:14:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲイユーザーのツイートから見える疾病像の把握（Characterizing Diseases and Disorders In Gay Users’ Tweets）</news:title>
   <news:publication_date>2026-04-20T03:14:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681318</loc>
  <lastmod>2026-04-20T02:23:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人物再識別のための多層因子分解ネットワーク（Multi-Level Factorisation Net for Person Re-Identification）</news:title>
   <news:publication_date>2026-04-20T02:23:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681316</loc>
  <lastmod>2026-04-20T02:22:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エゴセントリック映像における視線予測：タスク依存注意遷移の学習（Predicting Gaze in Egocentric Video by Learning Task-dependent Attention Transition）</news:title>
   <news:publication_date>2026-04-20T02:22:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681314</loc>
  <lastmod>2026-04-20T02:22:50Z</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>2026-04-20T02:22:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681312</loc>
  <lastmod>2026-04-20T02:22:31Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子もつれに導かれる機械学習アーキテクチャ（Entanglement-guided architectures of machine learning by quantum tensor network）</news:title>
   <news:publication_date>2026-04-20T02:22:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681310</loc>
  <lastmod>2026-04-20T02:22:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepWarpによるDNNベースの非線形変形（DeepWarp: DNN-based Nonlinear Deformation）</news:title>
   <news:publication_date>2026-04-20T02:22:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681308</loc>
  <lastmod>2026-04-20T02:22:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Machine Learning and Applied Linguistics (Machine Learning and Applied Linguistics)</news:title>
   <news:publication_date>2026-04-20T02:22:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681306</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>高次元最適化を読み解くための単純モデル：ガウスランダム場上の勾配降下法（Gradient descent in Gaussian random fields as a toy model for high-dimensional optimisation in deep learning）</news:title>
   <news:publication_date>2026-04-20T02:21:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681304</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像生成と改変のためのGAN技術比較（Comparing Generative Adversarial Network Techniques for Image Creation and Modification）</news:title>
   <news:publication_date>2026-04-20T01:30:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681302</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>動画における動きの規則性を教師なしで学ぶ敵対的枠組み（Adversarial Framework for Unsupervised Learning of Motion Dynamics in Videos）</news:title>
   <news:publication_date>2026-04-20T01:30:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681300</loc>
  <lastmod>2026-04-20T01:30:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近接ブロック座標降下法による深層ニューラルネットワーク学習（A Proximal Block Coordinate Descent Algorithm for Deep Neural Network Training）</news:title>
   <news:publication_date>2026-04-20T01:30:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681298</loc>
  <lastmod>2026-04-20T01:30:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習データの重み付け学習による頑健な深層学習（Learning to Reweight Examples for Robust Deep Learning）</news:title>
   <news:publication_date>2026-04-20T01:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681296</loc>
  <lastmod>2026-04-20T01:29:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチレンジ推論による機械読解（Multi-range Reasoning for Machine Comprehension）</news:title>
   <news:publication_date>2026-04-20T01:29:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681294</loc>
  <lastmod>2026-04-20T01:29:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Attention-based Adversarial Autoencoderによるマルチスケールネットワーク埋め込み（AAANE: Attention-based Adversarial Autoencoder for Multi-scale Network Embedding）</news:title>
   <news:publication_date>2026-04-20T01:29:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681292</loc>
  <lastmod>2026-04-20T01:29:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>写真のソーシャルメタデータから場所の景観美を予測できるか（Can We Predict the Scenic Beauty of Locations from Geo-tagged Flickr Images?）</news:title>
   <news:publication_date>2026-04-20T01:29:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681290</loc>
  <lastmod>2026-04-20T00:38:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小改変でCNNを欺く画像ステガノグラフィ（CNN Based Adversarial Embedding with Minimum Alteration for Image Steganography）</news:title>
   <news:publication_date>2026-04-20T00:38:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681288</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現豊かな音声合成におけるイントネーション転移の実現（Towards End-to-End Prosody Transfer for Expressive Speech Synthesis with Tacotron）</news:title>
   <news:publication_date>2026-04-20T00:37:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681286</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>パラメータ推定における制約の滑らかさの重要性（The Importance of Constraint Smoothness for Parameter Estimation in Computational Cognitive Modeling）</news:title>
   <news:publication_date>2026-04-20T00:37:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681284</loc>
  <lastmod>2026-04-20T00:37:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現を学習する「スタイルトークン」――エンドツーエンド音声合成の制御と転送 (Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis)</news:title>
   <news:publication_date>2026-04-20T00:37:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681282</loc>
  <lastmod>2026-04-20T00:37:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データセットに「説明書」を付ける考え方（Datasheets for Datasets）</news:title>
   <news:publication_date>2026-04-20T00:37:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681280</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>2026-04-20T00:36:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681278</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現転移学習による顔認識の少数サンプル問題への対処（Feature Transfer Learning for Face Recognition with Under-Represented Data）</news:title>
   <news:publication_date>2026-04-20T00:36:36Z</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>
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   <news:title>Successor Representationを用いたGVFにおける学習加速（Accelerating Learning in Constructive Predictive Frameworks with the Successor Representation）</news:title>
   <news:publication_date>2026-04-19T23:46:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681274</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>2026-04-19T23:45:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681272</loc>
  <lastmod>2026-04-19T23:45:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復低ランク近似によるCNN圧縮（Iterative Low-Rank Approximation for CNN Compression）</news:title>
   <news:publication_date>2026-04-19T23:45:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681270</loc>
  <lastmod>2026-04-19T23:45:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文単位の関連フィードバックが高リコール検索を変える（Evaluating Sentence-Level Relevance Feedback for High-Recall Information Retrieval）</news:title>
   <news:publication_date>2026-04-19T23:45:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681268</loc>
  <lastmod>2026-04-19T23:45:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepMood：携帯文字入力の振る舞いから感情状態を推定する手法（DeepMood: Modeling Mobile Phone Typing Dynamics for Mood Detection）</news:title>
   <news:publication_date>2026-04-19T23:45:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681266</loc>
  <lastmod>2026-04-19T23:44:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈外エラー検出の自動評価法（Automated Evaluation of Out-of-Context Errors）</news:title>
   <news:publication_date>2026-04-19T23:44:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681264</loc>
  <lastmod>2026-04-19T23:44:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フェーズ分離を学習する深層学習（Deep Learning Phase Segregation）</news:title>
   <news:publication_date>2026-04-19T23:44:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681262</loc>
  <lastmod>2026-04-19T22:53:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘルスケアのためのBroad Learning（Broad Learning for Healthcare）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681260</loc>
  <lastmod>2026-04-19T22:53:37Z</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>2026-04-19T22:53:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681258</loc>
  <lastmod>2026-04-19T22:52:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声から単語埋め込みを学ぶSpeech2Vec（Speech2Vec: A Sequence-to-Sequence Framework for Learning Word Embeddings from Speech）</news:title>
   <news:publication_date>2026-04-19T22:52:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681256</loc>
  <lastmod>2026-04-19T22:52:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ALBA製デジタルLLRFを用いたSolaris光源の運用経験（OPERATIONAL EXPERIENCE OF ALBA&amp;#039;S DIGITAL LLRF AT SOLARIS LIGHT SOURCE）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681254</loc>
  <lastmod>2026-04-19T22:52:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブロック単位手続き的学習とアニーリングした敵対的損失による画像修復（Image Inpainting using Block-wise Procedural Training with Annealed Adversarial Counterpart）</news:title>
   <news:publication_date>2026-04-19T22:52:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681252</loc>
  <lastmod>2026-04-19T22:52:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LiDAR深度補完を小さなモデルで実現する圧縮センシングの工夫（Deep Convolutional Compressed Sensing for LiDAR Depth Completion）</news:title>
   <news:publication_date>2026-04-19T22:52:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681250</loc>
  <lastmod>2026-04-19T22:51:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最後の四つの「予想」(Four Last &amp;#039;Conjectures&amp;#039;)</news:title>
   <news:publication_date>2026-04-19T22:51:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681248</loc>
  <lastmod>2026-04-19T22:00:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強い量子ダーウィニズムと強い独立性はスペクトラム放送構造に相当する（Strong Quantum Darwinism and Strong Independence is equivalent to Spectrum Broadcast Structure）</news:title>
   <news:publication_date>2026-04-19T22:00:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/681246</loc>
  <lastmod>2026-04-19T22:00:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>旋削工程におけるチャタ検出を拓く：機械学習とトポロジカルデータ解析の統合 (Chatter Classification in Turning using Machine Learning and Topological Data Analysis)</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>赤方偏移6付近における大規模なメタ銀河系電離背景の変動の証拠（Evidence for Large-Scale Fluctuations in the Metagalactic Ionizing Background Near Redshift Six）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>水の大容量・長期・深度超冷却を可能にした表面封止法（Long-term deep supercooling of large-volume water via surface sealing with immiscible liquids）</news:title>
   <news:publication_date>2026-04-19T21:58:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681240</loc>
  <lastmod>2026-04-19T21:58:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンドニューラル上の明示的推論による視覚質問応答（Explicit Reasoning over End-to-End Neural Architectures for Visual Question Answering）</news:title>
   <news:publication_date>2026-04-19T21:58:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681238</loc>
  <lastmod>2026-04-19T21:58:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バイザンチン耐性確率的勾配降下法（Byzantine Stochastic Gradient Descent）</news:title>
   <news:publication_date>2026-04-19T21:58:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681236</loc>
  <lastmod>2026-04-19T21:57:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの非テクスチャ変形面復元の学習（Learning to Reconstruct Texture-less Deformable Surfaces from a Single View）</news:title>
   <news:publication_date>2026-04-19T21:57:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681234</loc>
  <lastmod>2026-04-19T21:05:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>格差嫌悪が長期的な協力を促す仕組み（Inequity aversion improves cooperation in intertemporal social dilemmas）</news:title>
   <news:publication_date>2026-04-19T21:05:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681232</loc>
  <lastmod>2026-04-19T21:05:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Trace your sources in large-scale data（一環で見つける大規模データのソース追跡）</news:title>
   <news:publication_date>2026-04-19T21:05:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681230</loc>
  <lastmod>2026-04-19T21:04:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続と離散が混在する部分観測系に対する動的計画法（Dynamic Programming for POMDP with Jointly Discrete and Continuous State-Spaces）</news:title>
   <news:publication_date>2026-04-19T21:04:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681228</loc>
  <lastmod>2026-04-19T21:04:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内視鏡単一画像超解像のための効果的深層学習訓練（Effective deep learning training for single-image super-resolution in endomicroscopy exploiting video-registration-based reconstruction）</news:title>
   <news:publication_date>2026-04-19T21:04:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681226</loc>
  <lastmod>2026-04-19T21:03:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像と音声で出来事を特定する研究（Audio-Visual Event Localization in Unconstrained Videos）</news:title>
   <news:publication_date>2026-04-19T21:03:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681224</loc>
  <lastmod>2026-04-19T21:03:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声の分布意味論の難しさ（On the difﬁculty of a distributional semantics of spoken language）</news:title>
   <news:publication_date>2026-04-19T21:03:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681222</loc>
  <lastmod>2026-04-19T21:02:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非同期共有メモリにおける確率的勾配降下法の収束性（The Convergence of Stochastic Gradient Descent in Asynchronous Shared Memory）</news:title>
   <news:publication_date>2026-04-19T21:02:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681220</loc>
  <lastmod>2026-04-19T20:11:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理学者のための機械学習入門（A high-bias, low-variance introduction to Machine Learning for physicists）</news:title>
   <news:publication_date>2026-04-19T20:11:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681218</loc>
  <lastmod>2026-04-19T20:11:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>磁気シールド対応ハイブリッドトラップで大型ボース＝アインシュタイン凝縮を作る（Production of large Bose-Einstein condensates in a magnetic-shield-compatible hybrid trap）</news:title>
   <news:publication_date>2026-04-19T20:11:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681216</loc>
  <lastmod>2026-04-19T20:10:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドローン映像で「実世界の人密度」を推定する仕組み（Geometric and Physical Constraints for Drone-Based Head Plane Crowd Density Estimation）</news:title>
   <news:publication_date>2026-04-19T20:10:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681214</loc>
  <lastmod>2026-04-19T20:09:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サリエンシーを用いた敵対的摂動の検出（Detecting Adversarial Perturbations with Saliency）</news:title>
   <news:publication_date>2026-04-19T20:09:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681212</loc>
  <lastmod>2026-04-19T20:09:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮センシングMRIのための深い誤差補正ネットワーク（A Deep Error Correction Network for Compressed Sensing MRI）</news:title>
   <news:publication_date>2026-04-19T20:09:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681210</loc>
  <lastmod>2026-04-19T20:09:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的システムの因果モデリング（Causal Modeling of Dynamical Systems）</news:title>
   <news:publication_date>2026-04-19T20:09:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681208</loc>
  <lastmod>2026-04-19T20:08:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像注釈のための深層コンテキストネットワークアーキテクチャの学習（Learning Deep Context-Network Architectures for Image Annotation）</news:title>
   <news:publication_date>2026-04-19T20:08:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681206</loc>
  <lastmod>2026-04-19T19:16:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボット向け物体検出の学習を高速化する手法（Speeding-up Object Detection Training for Robotics with FALKON）</news:title>
   <news:publication_date>2026-04-19T19:16:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681204</loc>
  <lastmod>2026-04-19T19:16:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>配列データからタンパク質の構成モチーフを学習する（Learning protein constitutive motifs from sequence data）</news:title>
   <news:publication_date>2026-04-19T19:16:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681202</loc>
  <lastmod>2026-04-19T19:16:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医用画像における一般化と堅牢性の相克（Generalizability vs. Robustness: Adversarial Examples for Medical Imaging）</news:title>
   <news:publication_date>2026-04-19T19:16:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681200</loc>
  <lastmod>2026-04-19T19:16:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単段検出器と二段階検出器の精度と速度の最適化（Optimizing the Trade-off between Single-Stage and Two-Stage Deep Object Detectors using Image Difficulty Prediction）</news:title>
   <news:publication_date>2026-04-19T19:16:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681198</loc>
  <lastmod>2026-04-19T19:15:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習によるホログラフィック正規化（Holographic Renormalization with Machine learning）</news:title>
   <news:publication_date>2026-04-19T19:15:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681196</loc>
  <lastmod>2026-04-19T19:15:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人物再識別における姿勢駆動モデルと再ランキングの進展（Pose-Driven Re-Id and Re-Ranking Advances）</news:title>
   <news:publication_date>2026-04-19T19:15:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681194</loc>
  <lastmod>2026-04-19T19:15:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アラームベースの処方的プロセスモニタリング（Alarm-Based Prescriptive Process Monitoring）</news:title>
   <news:publication_date>2026-04-19T19:15:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681192</loc>
  <lastmod>2026-04-19T18:24:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時刻の伸縮に強くなるRNNの設計（CAN RECURRENT NEURAL NETWORKS WARP TIME?）</news:title>
   <news:publication_date>2026-04-19T18:24:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681190</loc>
  <lastmod>2026-04-19T18:24:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による医用画像セグメンテーションの実用化軸（Deep learning and its application to medical image segmentation）</news:title>
   <news:publication_date>2026-04-19T18:24:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681188</loc>
  <lastmod>2026-04-19T18:23:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コアセットのための決定的点過程（Determinantal Point Processes for Coresets）</news:title>
   <news:publication_date>2026-04-19T18:23:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681186</loc>
  <lastmod>2026-04-19T18:23:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間時間規則化相関フィルタによる視覚追跡の高速化と頑健化（Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking）</news:title>
   <news:publication_date>2026-04-19T18:23:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681184</loc>
  <lastmod>2026-04-19T18:22:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>領域フィルタリング相関追跡（Region-filtering Correlation Tracking）</news:title>
   <news:publication_date>2026-04-19T18:22:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681182</loc>
  <lastmod>2026-04-19T18:22:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピラミッドステレオマッチングネットワーク（Pyramid Stereo Matching Network）</news:title>
   <news:publication_date>2026-04-19T18:22:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681180</loc>
  <lastmod>2026-04-19T18:22:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヤコビアン正則化によるDNNの敵対的耐性向上（Improving DNN Robustness to Adversarial Attacks using Jacobian Regularization）</news:title>
   <news:publication_date>2026-04-19T18:22:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681178</loc>
  <lastmod>2026-04-19T17:31:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な全域最適化におけるユニバーサルクリギング（On Efficient Global Optimization via Universal Kriging Surrogate Models）</news:title>
   <news:publication_date>2026-04-19T17:31:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681176</loc>
  <lastmod>2026-04-19T17:30:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高コスト評価関数を扱うベイズ最適化（Bayesian Optimization with Expensive Integrands）</news:title>
   <news:publication_date>2026-04-19T17:30:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681174</loc>
  <lastmod>2026-04-19T17:30:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速で高精度、かつ軽量な単一画像超解像を実現するCARN（Fast, Accurate and Lightweight Super-Resolution with Cascading Residual Network）</news:title>
   <news:publication_date>2026-04-19T17:30:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681172</loc>
  <lastmod>2026-04-19T17:30:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>履歴モデルを利用したGAN訓練（Fictitious GAN: Training GANs with Historical Models）</news:title>
   <news:publication_date>2026-04-19T17:30:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681170</loc>
  <lastmod>2026-04-19T17:29:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推薦が利用者関心に与える影響を考慮した学習（Learning Recommendations While Influencing Interests）</news:title>
   <news:publication_date>2026-04-19T17:29:56Z</news:publication_date>
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   <news:title>Lifting Layersの理論と応用（Lifting Layers: Analysis and Applications）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>Studio OusiaのQuiz Bowl質問応答システム（Studio Ousia’s Quiz Bowl Question Answering System）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Prior-Model Guided Depth-enhanced NetworkによるRGB-D顕著領域検出（PDNet: Prior-Model Guided Depth-enhanced Network for Salient Object Detection）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>サンプルアンサンブル遺伝的進化ネットワーク（Sample-Ensemble Genetic Evolutionary Network）</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>イメージングセンサー向け時空間ニューロン処理基盤（Hardware based Spatio-Temporal Neural Processing Backend for Imaging Sensors: Towards a Smart Camera）</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>Version Space の大きさで学習を評価する手法（A Concept Learning Tool Based On Calculating Version Space Cardinality）</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>疑似天体信号の分類にWide Residual Networksを用いる研究（Classification of simulated radio signals using Wide Residual Networks for use in the search for extra-terrestrial intelligence）</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>音声の分離性能と現実一般化の課題（Generalization Challenges for Neural Architectures in Audio Source Separation）</news:title>
   <news:publication_date>2026-04-19T16:36:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MobileNetを量子化に強くする分離畳み込みの工夫（A Quantization-Friendly Separable Convolution for MobileNets）</news:title>
   <news:publication_date>2026-04-19T16:36:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepDRRが切り開く術中透視への機械学習の道（DeepDRR – A Catalyst for Machine Learning in Fluoroscopy-guided Procedures）</news:title>
   <news:publication_date>2026-04-19T15:45:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>クエリ最適化のための状態表現学習（Learning State Representations for Query Optimization with Deep Reinforcement 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:publication_date>2026-04-19T15:44:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>深層多変量プロビットモデルのエンドツーエンド学習（End-to-End Learning for the Deep Multivariate Probit Model）</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>ハイパーグラフの曲率とマルチマージナル最適輸送（Curvature of Hypergraphs via Multi-Marginal Optimal Transport）</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>顕著部位に基づく重み付き双線形符号化による人物再識別（Weighted Bilinear Coding over Salient Body Parts for Person Re-identiﬁcation）</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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