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   <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>
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   <news:title>DeepWarpによるDNNベースの非線形変形（DeepWarp: DNN-based Nonlinear Deformation）</news:title>
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   <news:title>Machine Learning and Applied Linguistics (Machine Learning and Applied Linguistics)</news:title>
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   <news:genres>Blog</news:genres>
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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>
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    <news:language>ja</news:language>
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   <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>
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   <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>
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    <news:language>ja</news:language>
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   <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>
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   <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>
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    <news:language>ja</news:language>
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   <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>
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    <news:language>ja</news:language>
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   <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>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-20T01:29:25Z</lastmod>
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   <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>
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  <lastmod>2026-04-20T00:38:39Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>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>
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   <news:genres>Blog</news:genres>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>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>
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   <news:genres>Blog</news:genres>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>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>
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   <news:genres>Blog</news:genres>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>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>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-20T00:37:08Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>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>
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  <lastmod>2026-04-20T00:36:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>FPGA上でのハイブリッド高速畳み込みによる顔認識高速化（Face Recognition with Hybrid Efficient Convolution Algorithms on FPGAs）</news:title>
   <news:publication_date>2026-04-20T00:36:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-20T00:36:36Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>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>
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  <lastmod>2026-04-19T23:46:05Z</lastmod>
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    <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>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>層状自己組織化マップによるパターン解析（Pattern Analysis with Layered Self-Organizing Maps）</news:title>
   <news:publication_date>2026-04-19T23:45:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-19T23:45:38Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>反復低ランク近似によるCNN圧縮（Iterative Low-Rank Approximation for CNN Compression）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-19T23:45:14Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>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>
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  <lastmod>2026-04-19T23:45:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <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>
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  <lastmod>2026-04-19T23:44:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <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>
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  <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>
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  <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>
   <news:publication_date>2026-04-19T22:53:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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  <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>
   <news:title>Twitterにおける敵意あるユーザーの特徴づけと検出（Characterizing and Detecting Hateful Users on Twitter）</news:title>
   <news:publication_date>2026-04-19T22:53:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <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>
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  <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>
   </news:publication>
   <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>
   <news:publication_date>2026-04-19T22:52:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <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>
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   <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>
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  <lastmod>2026-04-19T22:52:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <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>
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  <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>
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  <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>
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   <news:publication_date>2026-04-19T22:00:41Z</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>2026-04-19T22:00:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>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>
   <news:publication_date>2026-04-19T21:59:13Z</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>2026-04-19T21:58:22Z</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>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>
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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>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>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一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>
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  <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>
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  <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>
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  <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>
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  <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>
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  <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>
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  <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>
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   <news:publication_date>2026-04-19T21:02:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <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>
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   <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>
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   <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>
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   <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>
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 </url>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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 </url>
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    <news:name>AI Benchmark Research</news:name>
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 </url>
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 </url>
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    <news:name>AI Benchmark Research</news:name>
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 </url>
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 </url>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/681102</loc>
  <lastmod>2026-04-19T12:59:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話エージェントの急速な変化（The Rapidly Changing Landscape of Conversational Agents）</news:title>
   <news:publication_date>2026-04-19T12:59:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681100</loc>
  <lastmod>2026-04-19T12:59:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガイド付き画像インペインティング（Guided Image Inpainting: Replacing an Image Region by Pulling Content from Another Image）</news:title>
   <news:publication_date>2026-04-19T12:59:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681098</loc>
  <lastmod>2026-04-19T12:59:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を幾何学で解きほぐす：反復射影のアプローチ（DEMYSTIFYING DEEP LEARNING: A GEOMETRIC APPROACH TO ITERATIVE PROJECTIONS）</news:title>
   <news:publication_date>2026-04-19T12:59:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681096</loc>
  <lastmod>2026-04-19T12:59:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非可換モノポールとQCDにおける閉じ込めとXSB（Confinement and XSB in QCD: Mysteries and beauty of soliton dynamics in nonAbelian gauge theories）</news:title>
   <news:publication_date>2026-04-19T12:59:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681094</loc>
  <lastmod>2026-04-19T12:07:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロヒンギャ関連コメントの感情分析に関するSVM研究（Sentiment Analysis of Comments on Rohingya Movement with Support Vector Machine）</news:title>
   <news:publication_date>2026-04-19T12:07:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681092</loc>
  <lastmod>2026-04-19T12:07:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PlaneMatchによる平面コプラナリ予測で堅牢なRGB-D再構成を実現する（PlaneMatch: Patch Coplanarity Prediction for Robust RGB-D Reconstruction）</news:title>
   <news:publication_date>2026-04-19T12:07:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681090</loc>
  <lastmod>2026-04-19T12:07:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深部焦点化タイムディスタンス・ヘリオセイズモロジーにおける伝播時間と振幅測定の比較（Comparison of Travel-Time and Amplitude Measurements for Deep-Focusing Time–Distance Helioseismology）</news:title>
   <news:publication_date>2026-04-19T12:07:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681088</loc>
  <lastmod>2026-04-19T12:06:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>濃密接続ピラミッド除霧ネットワークの要点（Densely Connected Pyramid Dehazing Network）</news:title>
   <news:publication_date>2026-04-19T12:06:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681086</loc>
  <lastmod>2026-04-19T12:06:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DOP: 近似価値評価を用いた深い楽観的計画（DOP: Deep Optimistic Planning with Approximate Value Function Evaluation）</news:title>
   <news:publication_date>2026-04-19T12:06:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681084</loc>
  <lastmod>2026-04-19T12:06:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類層におけるReLUの応用—出力層を直線化する試み（Deep Learning using Rectified Linear Units (ReLU))</news:title>
   <news:publication_date>2026-04-19T12:06:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681082</loc>
  <lastmod>2026-04-19T12:05:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミラー層化正則化によるモデル整合性の理論的整理（Model Consistency for Learning with Mirror-Stratifiable Regularizers）</news:title>
   <news:publication_date>2026-04-19T12:05:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681080</loc>
  <lastmod>2026-04-19T11:14:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化出力の放棄学習による意見予測の精度向上（Structured Output Learning with Abstention: Application to Accurate Opinion Prediction）</news:title>
   <news:publication_date>2026-04-19T11:14:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681078</loc>
  <lastmod>2026-04-19T11:14:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gradient DescentがReLUネットワーク特徴を量子化する（Gradient Descent Quantizes ReLU Network Features）</news:title>
   <news:publication_date>2026-04-19T11:14:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681076</loc>
  <lastmod>2026-04-19T11:14:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>隠れパラメータの決定的割当による学習（Learning through deterministic assignment of hidden parameters）</news:title>
   <news:publication_date>2026-04-19T11:14:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681074</loc>
  <lastmod>2026-04-19T11:13:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光学データから銀河の中性水素量を予測する機械学習（Predicting the Neutral Hydrogen Content of Galaxies From Optical Data Using Machine Learning）</news:title>
   <news:publication_date>2026-04-19T11:13:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681072</loc>
  <lastmod>2026-04-19T11:13:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深部流体注入に伴う誘発地震に対する自律的意思決定（Autonomous decision-making against induced seismicity in deep fluid injections）</news:title>
   <news:publication_date>2026-04-19T11:13:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681070</loc>
  <lastmod>2026-04-19T11:13:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ネットワークは何を見ているか（What do Deep Networks Like to See?）</news:title>
   <news:publication_date>2026-04-19T11:13:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681068</loc>
  <lastmod>2026-04-19T11:13:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>優先度付きマルチビュー深度マップ生成と信頼度予測（Prioritized Multi-View Stereo Depth Map Generation Using Confidence Prediction）</news:title>
   <news:publication_date>2026-04-19T11:13:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681066</loc>
  <lastmod>2026-04-19T10:22:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光モードの場分布を機械学習で分類する手法（Machine learning classification for field distributions of photonic modes）</news:title>
   <news:publication_date>2026-04-19T10:22:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681064</loc>
  <lastmod>2026-04-19T10:21:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子イジング臨界付近のクエンチとニューラルネットワークの限界（Quenches near Ising quantum criticality as a challenge for artificial neural networks）</news:title>
   <news:publication_date>2026-04-19T10:21:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681062</loc>
  <lastmod>2026-04-19T10:20:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>がん臨床試験における適格判定を自動化する手法（Learning Eligibility in Cancer Clinical Trials using Deep Neural Networks）</news:title>
   <news:publication_date>2026-04-19T10:20:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681060</loc>
  <lastmod>2026-04-19T10:19:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>見えない関節を仮想世界で学習して検出・追跡する技術（Learning to Detect and Track Visible and Occluded Body Joints in a Virtual World）</news:title>
   <news:publication_date>2026-04-19T10:19:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681058</loc>
  <lastmod>2026-04-19T10:18:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>永続エントロピーの安定性と要約関数の提案（On the stability of persistent entropy and new summary functions for Topological Data Analysis）</news:title>
   <news:publication_date>2026-04-19T10:18:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681056</loc>
  <lastmod>2026-04-19T10:18:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安全な探索を実現する学習型モデル予測制御（Learning-based Model Predictive Control for Safe Exploration）</news:title>
   <news:publication_date>2026-04-19T10:18:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681054</loc>
  <lastmod>2026-04-19T10:18:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインソーシャルネットワークにおける偽プロフィールの実態と法的対策（Sneak into Devil’s Colony — Study of Fake Profiles in Online Social Networks and the Cyber Law）</news:title>
   <news:publication_date>2026-04-19T10:18:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681052</loc>
  <lastmod>2026-04-19T09:25:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話者クラスタリングにおけるCNNと音声前処理の実践的考察（Speaker Clustering With Neural Networks And Audio Processing）</news:title>
   <news:publication_date>2026-04-19T09:25:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681050</loc>
  <lastmod>2026-04-19T09:25:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>緩やかな銀河群における銀河間水素ガスの全容解明（Galaxy interactions in loose galaxy groups: KAT-7 and VLA H i Observations of the IC 1459 group）</news:title>
   <news:publication_date>2026-04-19T09:25:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681048</loc>
  <lastmod>2026-04-19T09:24:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2D関節情報から学ぶ教師なし3D人体姿勢推定（Unsupervised Adversarial Learning of 3D Human Pose from 2D Joint Locations）</news:title>
   <news:publication_date>2026-04-19T09:24:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681046</loc>
  <lastmod>2026-04-19T09:24:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PersonLab: 人物の姿勢推定とインスタンス分割を統合するボトムアップ手法（PersonLab: Person Pose Estimation and Instance Segmentation with a Bottom-Up, Part-Based, Geometric Embedding Model）</news:title>
   <news:publication_date>2026-04-19T09:24:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681044</loc>
  <lastmod>2026-04-19T09:24:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シャノンのチャネルから意味的チャネルへ（From Shannon’s Channel to Semantic Channel via New Bayes’ Formulas for Machine Learning）</news:title>
   <news:publication_date>2026-04-19T09:24:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681042</loc>
  <lastmod>2026-04-19T09:24:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形流体のためのスパース畳み込みに基づくマルコフモデル（Sparse Convolution-based Markov Models for Nonlinear Fluid Flows）</news:title>
   <news:publication_date>2026-04-19T09:24:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681040</loc>
  <lastmod>2026-04-19T09:24:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車載ネットワークにおける安全なメッセージ伝播の位相的アプローチ (A Topological Approach to Secure Message Dissemination in Vehicular Networks)</news:title>
   <news:publication_date>2026-04-19T09:24:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681038</loc>
  <lastmod>2026-04-19T08:33:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高品質物体検出のための単発双方向ピラミッドネットワーク（Single-Shot Bidirectional Pyramid Networks for High-Quality Object Detection）</news:title>
   <news:publication_date>2026-04-19T08:33:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681036</loc>
  <lastmod>2026-04-19T08:32:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>陽性・未ラベル畳み込みニューラルネットワークによるクライオ電子顕微鏡画像の粒子選別（Positive-unlabeled convolutional neural networks for particle picking in cryo-electron micrographs）</news:title>
   <news:publication_date>2026-04-19T08:32:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681034</loc>
  <lastmod>2026-04-19T08:32:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による低次元化で見える遷移乱流の本質（Construction of low-dimensional system reproducing low-Reynolds-number turbulence）</news:title>
   <news:publication_date>2026-04-19T08:32:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681032</loc>
  <lastmod>2026-04-19T08:31:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一相の性質から複数の相転移を予測する機械学習（Extrapolating quantum observables with machine learning: Inferring multiple phase transitions from properties of a single phase）</news:title>
   <news:publication_date>2026-04-19T08:31:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681030</loc>
  <lastmod>2026-04-19T08:31:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Residual Networksの安定性と凸/凹分解が示す学習の本質（Residual Networks: Lyapunov Stability and Convex Decomposition）</news:title>
   <news:publication_date>2026-04-19T08:31:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681028</loc>
  <lastmod>2026-04-19T08:31:27Z</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3D人体姿勢推定を変える手法（Deep Pose Consensus Networks）</news:title>
   <news:publication_date>2026-04-19T08:31:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681026</loc>
  <lastmod>2026-04-19T08:30:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>曲率情報を用いた確率的分散最適化の加速（SUCAG: Stochastic Unbiased Curvature-aided Gradient Method for Distributed Optimization）</news:title>
   <news:publication_date>2026-04-19T08:30:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681024</loc>
  <lastmod>2026-04-19T07:40:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANに制約を直接組み込む手法とその実用性（Enforcing constraints for interpolation and extrapolation in Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-04-19T07:40:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681022</loc>
  <lastmod>2026-04-19T07:39:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LiDARとカメラの外部較正を自己学習で解く（CalibNet: Geometrically Supervised Extrinsic Calibration using 3D Spatial Transformer Networks）</news:title>
   <news:publication_date>2026-04-19T07:39:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681020</loc>
  <lastmod>2026-04-19T07:39:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復ブースティングによる確率密度推定の再考（Boosted Density Estimation Remastered）</news:title>
   <news:publication_date>2026-04-19T07:39:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681018</loc>
  <lastmod>2026-04-19T07:38:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習によるホログラフィック像復元の焦点拡張（Extended depth-of-field in holographic image reconstruction using deep learning based auto-focusing and phase-recovery）</news:title>
   <news:publication_date>2026-04-19T07:38:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681016</loc>
  <lastmod>2026-04-19T07:38:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力ごとの反復計算を問う：Repeat‑RNNとACTの比較（Comparing Fixed and Adaptive Computation Time for Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-04-19T07:38:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681014</loc>
  <lastmod>2026-04-19T07:38:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>指紋ベース屋内位置推定の学習関数（Learning the Localization Function）</news:title>
   <news:publication_date>2026-04-19T07:38:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681012</loc>
  <lastmod>2026-04-19T07:37:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検閲データからの誤学習（Mislearning from Censored Data: The Gambler’s Fallacy and Other Correlational Mistakes in Optimal-Stopping Problems）</news:title>
   <news:publication_date>2026-04-19T07:37:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681010</loc>
  <lastmod>2026-04-19T06:47:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頑健なブラインドデコンボリューションとMirror Descent（Robust Blind Deconvolution via Mirror Descent）</news:title>
   <news:publication_date>2026-04-19T06:47:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681008</loc>
  <lastmod>2026-04-19T06:46:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク依存深層LDAプルーニング（Task-dependent Deep LDA pruning of neural networks）</news:title>
   <news:publication_date>2026-04-19T06:46:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681006</loc>
  <lastmod>2026-04-19T06:46:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Seglearnによる時系列学習の実務活用（Seglearn: A Python Package for Learning Sequences and Time Series）</news:title>
   <news:publication_date>2026-04-19T06:46:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681004</loc>
  <lastmod>2026-04-19T06:45:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>速度変化に頑強な埋め込み学習（T-RECS: Training for Rate-Invariant Embeddings by Controlling Speed for Action Recognition）</news:title>
   <news:publication_date>2026-04-19T06:45:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681002</loc>
  <lastmod>2026-04-19T06:45:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多視点・多クラス物体姿勢推定の統一フレームワーク（A Unified Framework for Multi-View Multi-Class Object Pose Estimation）</news:title>
   <news:publication_date>2026-04-19T06:45:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681000</loc>
  <lastmod>2026-04-19T06:44:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラッタ中の操作におけるリセディングホライズン計画と学習価値関数（Planning with a Receding Horizon for Manipulation in Clutter using a Learned Value Function）</news:title>
   <news:publication_date>2026-04-19T06:44:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680998</loc>
  <lastmod>2026-04-19T06:44:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間データ圧縮の実務的手法──密度ベースクラスタリングによる代表点抽出（Clustering to Reduce Spatial Data Set Size）</news:title>
   <news:publication_date>2026-04-19T06:44:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680996</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>黒洞の鐘（A Carillon of Black Holes）</news:title>
   <news:publication_date>2026-04-19T05:52:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680994</loc>
  <lastmod>2026-04-19T05:51:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インクリメンタルな学習を学ぶ—逐次タスクで学習アルゴリズムを最適化する（Incremental Learning-to-Learn with Statistical Guarantees）</news:title>
   <news:publication_date>2026-04-19T05:51:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680992</loc>
  <lastmod>2026-04-19T05:51:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン投票時における増強されたヒトの影響（Influence of augmented humans in online interactions during voting events）</news:title>
   <news:publication_date>2026-04-19T05:51:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680990</loc>
  <lastmod>2026-04-19T05:50:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フラクタル状プラズモニック自己相似材料の近赤外プラズマ周波数制御（Fractal-like plasmonic self-similar material with a tailorable plasma frequency in the near-infrared）</news:title>
   <news:publication_date>2026-04-19T05:50:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680988</loc>
  <lastmod>2026-04-19T05:50:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>固有分解を使わない深層網の訓練法（Eigendecomposition-free Training of Deep Networks with Zero Eigenvalue-based Losses）</news:title>
   <news:publication_date>2026-04-19T05:50:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680986</loc>
  <lastmod>2026-04-19T05:49:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全体属性制御による確率的ビデオ生成（Probabilistic Video Generation using Holistic Attribute Control）</news:title>
   <news:publication_date>2026-04-19T05:49:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680984</loc>
  <lastmod>2026-04-19T05:49:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジェット電荷と機械学習（Jet Charge and Machine Learning）</news:title>
   <news:publication_date>2026-04-19T05:49:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680982</loc>
  <lastmod>2026-04-19T04:57:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>類似要素と完全グラフ上のメトリックラベリング（Similar Elements and Metric Labeling on Complete Graphs）</news:title>
   <news:publication_date>2026-04-19T04:57:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680980</loc>
  <lastmod>2026-04-19T04:56:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散強化学習の双対プライマル解法（Primal-Dual Algorithm for Distributed Reinforcement Learning: Distributed GTD）</news:title>
   <news:publication_date>2026-04-19T04:56:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680978</loc>
  <lastmod>2026-04-19T04:56:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識グラフと意味埋め込みによるゼロショット認識（Zero-shot Recognition via Semantic Embeddings and Knowledge Graphs）</news:title>
   <news:publication_date>2026-04-19T04:56:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680976</loc>
  <lastmod>2026-04-19T04:55:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>下部マントルに残るケイ酸塩濃縮領域の持続性（Persistence of Strong Silica-Enriched Domains in the Earth’s Lower Mantle）</news:title>
   <news:publication_date>2026-04-19T04:55:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680974</loc>
  <lastmod>2026-04-19T04:55:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stacked Cross Attentionによる画像と文の照合（Stacked Cross Attention for Image-Text Matching）</news:title>
   <news:publication_date>2026-04-19T04:55:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680972</loc>
  <lastmod>2026-04-19T04:54:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼深度推定を異種データセットで学ぶ（Monocular Depth Estimation by Learning from Heterogeneous Datasets）</news:title>
   <news:publication_date>2026-04-19T04:54:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680970</loc>
  <lastmod>2026-04-19T04:54:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブートストラップによるランダム化最小二乗法の誤差推定（Error Estimation for Randomized Least-Squares Algorithms via the Bootstrap）</news:title>
   <news:publication_date>2026-04-19T04:54:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680968</loc>
  <lastmod>2026-04-19T04:02:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力信号を守る防御：Structure-to-Signal Autoencodersによる敵対的防御（Adversarial Defense based on Structure-to-Signal Autoencoders）</news:title>
   <news:publication_date>2026-04-19T04:02:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680966</loc>
  <lastmod>2026-04-19T04:02:10Z</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/680964</loc>
  <lastmod>2026-04-19T04:01:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムフォレストのバイアス低減のためのワンステップ・ブースト（Boosting Random Forests to Reduce Bias; One-Step Boosted Forest and its Variance Estimate）</news:title>
   <news:publication_date>2026-04-19T04:01:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-19T04:01:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習の情報理論的解釈（Information Theoretic Interpretation of Deep Learning）</news:title>
   <news:publication_date>2026-04-19T04:01:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/680960</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-19T04:01:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680958</loc>
  <lastmod>2026-04-19T04:01:12Z</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>2026-04-19T04:01:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-19T04:01:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バグの「自然さ」を再考する：再帰型ニューラルネットワークによる解析（Exploring the Naturalness of Buggy Code with Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-04-19T04:01:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680954</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:publication_date>2026-04-19T03:09:56Z</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>定常ステップサイズ下におけるランダム再シャッフル学習（Stochastic Learning under Random Reshuffling with Constant Step-sizes）</news:title>
   <news:publication_date>2026-04-19T03:09:43Z</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>
   <news:title>堅牢な単調逐次最大化（Resilient Monotone Sequential Maximization）</news:title>
   <news:publication_date>2026-04-19T03:09:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>End-to-End Video Captioning with Multitask Reinforcement Learning（End-to-End Video Captioning with Multitask Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-19T03:09:06Z</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>アイテム選別のためのクラウドと機械の協働（Crowd-Machine Collaboration for Item Screening）</news:title>
   <news:publication_date>2026-04-19T03:09:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680944</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>故障検出性の高いミューテント選択（Selecting Fault Revealing Mutants）</news:title>
   <news:publication_date>2026-04-19T03:08:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680942</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>HATSによるイベントベース画像認識の堅牢化（HATS: Histograms of Averaged Time Surfaces for Robust Event-based Object Classification）</news:title>
   <news:publication_date>2026-04-19T03:08:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680940</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>標本画像から種と形質を読み取る試み（Taxon and trait recognition from digitized herbarium specimens using deep convolutional neural networks）</news:title>
   <news:publication_date>2026-04-19T02:17:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>血液検査から創傷部感染を非教師ありで見抜く多変量時系列カーネル法（An Unsupervised Multivariate Time Series Kernel Approach for Identifying Patients with Surgical Site Infection from Blood Samples）</news:title>
   <news:publication_date>2026-04-19T02:17:13Z</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>時期依存のエンティティ要素推薦—イベント中心の複数モデル（Multiple Models for Recommending Temporal Aspects of Entities）</news:title>
   <news:publication_date>2026-04-19T02:16:58Z</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>時系列トピックモデルの拡張とスケーラブル推論（Scalable Generalized Dynamic Topic Models）</news:title>
   <news:publication_date>2026-04-19T02:16:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入院再入院予測におけるデータカテゴリの貢献（Contribution of Data Categories to Readmission Prediction Accuracy）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズネットワークの効率的なサンプリングと構造学習（Efficient Sampling and Structure Learning of Bayesian Networks）</news:title>
   <news:publication_date>2026-04-19T02:15:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量時系列の表現と分類を変えるリザバー・モデル空間（Reservoir computing approaches for representation and classification of multivariate time series）</news:title>
   <news:publication_date>2026-04-19T02:14:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680926</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Expeditious Generation of Knowledge Graph Embeddings（Expeditious Generation of Knowledge Graph Embeddings）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/680924</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>ベクトル値カーネル空間におけるマルチビュー計量学習 (Multi-view Metric Learning in Vector-valued Kernel Spaces)</news:title>
   <news:publication_date>2026-04-19T01:19:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680922</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>GANの理論的性質（Some Theoretical Properties of GANs）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-19T01:19:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680918</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>2026-04-19T01:19:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680916</loc>
  <lastmod>2026-04-19T01:18:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>骨格データからの行動認識における深層残差ネットワークの活用（Exploiting deep residual networks for human action recognition from skeletal data）</news:title>
   <news:publication_date>2026-04-19T01:18:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680914</loc>
  <lastmod>2026-04-19T01:18:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>耳認証のドメイン適応と二段階ファインチューニング（Domain Adaptation for Ear Recognition using Deep CNNs）</news:title>
   <news:publication_date>2026-04-19T01:18:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680912</loc>
  <lastmod>2026-04-19T00:27:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース系同定のサンプル複雑性（Sample Complexity of Sparse System Identification Problem）</news:title>
   <news:publication_date>2026-04-19T00:27:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680910</loc>
  <lastmod>2026-04-19T00:27:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNNを訓練して空間局在を学ばせると格子状表現が自発的に現れる（EMERGENCE OF GRID-LIKE REPRESENTATIONS BY TRAINING RECURRENT NEURAL NETWORKS TO PERFORM SPATIAL LOCALIZATION）</news:title>
   <news:publication_date>2026-04-19T00:27:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680908</loc>
  <lastmod>2026-04-19T00:27:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ρ-hot辞書埋め込みと二層LSTMによる感情解析の進展（ρ-hot Lexicon Embedding-based Two-level LSTM for Sentiment Analysis）</news:title>
   <news:publication_date>2026-04-19T00:27:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680906</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>適応型逐次MCMCによる状態とパラメータ同時推定（Adaptive Sequential MCMC for Combined State and Parameter Estimation）</news:title>
   <news:publication_date>2026-04-19T00:26:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680904</loc>
  <lastmod>2026-04-19T00:26:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>先を見てから飛べ（Look Before You Leap: Bridging Model-Free and Model-Based Reinforcement Learning for Planned-Ahead Vision-and-Language Navigation）</news:title>
   <news:publication_date>2026-04-19T00:26:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680902</loc>
  <lastmod>2026-04-19T00:26:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNの形状バイアスの検証（Assessing Shape Bias Property of Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-04-19T00:26:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680900</loc>
  <lastmod>2026-04-19T00:26:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PyramidBoxによる文脈支援型シングルショット顔検出の要点（PyramidBox: A Context-assisted Single Shot Face Detector）</news:title>
   <news:publication_date>2026-04-19T00:26:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680898</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>回転予測による教師なし表現学習（Unsupervised Representation Learning by Predicting Image Rotations）</news:title>
   <news:publication_date>2026-04-18T23:34:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680896</loc>
  <lastmod>2026-04-18T23:34:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム初期化で解ける位相復元 — Gradient Descent with Random Initialization: Fast Global Convergence for Nonconvex Phase Retrieval（Gradient Descent with Random Initialization: Fast Global Convergence for Nonconvex Phase Retrieval）</news:title>
   <news:publication_date>2026-04-18T23:34:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680894</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>Attention on Attention: Visual Question Answeringの注意機構改良がもたらす実務上の示唆（Attention on Attention: Architectures for Visual Question Answering）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680892</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>Generative Adversarial Talking Head（Generative Adversarial Talking Head: Bringing Portraits to Life with a Weakly Supervised Neural Network）</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>データ駆動型計算手法：パラメータとオペレータ推定（Data-Driven Computational Methods: Parameter and Operator Estimations）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-18T23:32:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news: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: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>2026-04-18T22:40:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-18T22:40:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>PaaSクラウドのビジネス視点（PaaS Cloud — The Business Perspective）</news:title>
   <news:publication_date>2026-04-18T22:39:41Z</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>室温バルク半導体における励起子制御とコヒーレント歪みパルス（Exciton Control in a Room-Temperature Bulk Semiconductor with Coherent Strain Pulses）</news:title>
   <news:publication_date>2026-04-18T21:48:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>FPGA上での効率的なRNN実装：ブロック巡回行列による圧縮と加速（EFFICIENT RECURRENT NEURAL NETWORKS USING STRUCTURED MATRICES IN FPGAs）</news:title>
   <news:publication_date>2026-04-18T21:48:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高相関設計と整列性を持つ回帰問題のグラフベース正則化（Graph-based regularization for regression problems with alignment and highly-correlated designs）</news:title>
   <news:publication_date>2026-04-18T21:48:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>CADから学ぶロボット組立（Learning Robotic Assembly from CAD）</news:title>
   <news:publication_date>2026-04-18T21:47:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-18T21:47:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ランダム化EMによるドメイン適応（Domain Adaptation with Randomized Expectation Maximization）</news:title>
   <news:publication_date>2026-04-18T21:47:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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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>モバイルロボット応用における深層学習技術の総覧（A Survey of Deep Learning Techniques for Mobile Robot Applications）</news:title>
   <news:publication_date>2026-04-18T20:55:53Z</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>オンライン学習における十分統計とBurkholder法（Online Learning: Sufficient Statistics and the Burkholder Method）</news:title>
   <news:publication_date>2026-04-18T20:48:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プログラム的弱い教師あり学習によるマルチエージェント軌跡生成（Generating Multi-Agent Trajectories Using Programmatic Weak Supervision）</news:title>
   <news:publication_date>2026-04-18T20:47:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在変数ガウス過程によるメタ強化学習（Meta Reinforcement Learning with Latent Variable Gaussian Processes）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680840</loc>
  <lastmod>2026-04-18T19:53:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>次元学習を探る：罰則付き確率的主成分分析による次元推定（Exploring dimension learning via a penalized probabilistic principal component analysis）</news:title>
   <news:publication_date>2026-04-18T19:53:57Z</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>カテゴリ固有メッシュ再構築の学習（Learning Category-Specific Mesh Reconstruction from Image Collections）</news:title>
   <news:publication_date>2026-04-18T19:53:49Z</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>有界次数DAGにおけるブロードキャスト（Broadcasting on Bounded Degree DAGs）</news:title>
   <news:publication_date>2026-04-18T19:52:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-18T19:52:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>p波相互作用フェルミ気体における三体散逸のユニタリ制限挙動（Unitarity-limited behavior of three-body collisions in a p-wave interacting Fermi gas）</news:title>
   <news:publication_date>2026-04-18T19:52:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-04-18T19:52:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>線毛運動解析のためのスタック型ニューラルネットワーク（STACKED NEURAL NETWORKS FOR END-TO-END CILIARY MOTION 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>
   </news:publication>
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   <news:publication_date>2026-04-18T19:52:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データベース内学習AC/DCの実務的意義（AC/DC: In-Database Learning Thunderstruck）</news:title>
   <news:publication_date>2026-04-18T19:00:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ステレオと単眼深度推定の自己教師学習による融合（Fusion of stereo and still monocular depth estimates）</news:title>
   <news:publication_date>2026-04-18T18:51:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的価格設定と競争環境での学習（Dynamic Pricing and Learning with Competition: Insights from the Dynamic Pricing Challenge）</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>DeepGaugeが示す深層学習テストの定量基準（DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-18T18:50:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然勾配を用いた深層Q学習（Natural Gradient Deep Q-learning）</news:title>
   <news:publication_date>2026-04-18T18:50:51Z</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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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>視覚質問応答に説明を加える手法（VQA-E: Explaining, Elaborating, and Enhancing Your Answers for Visual Questions）</news:title>
   <news:publication_date>2026-04-18T17:58:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680812</loc>
  <lastmod>2026-04-18T17:58:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-18T17:58:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680810</loc>
  <lastmod>2026-04-18T17:58:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MLtunerによるトレーニング自動チューニングの実務的意義（MLtuner: System Support for Automatic Machine Learning Tuning）</news:title>
   <news:publication_date>2026-04-18T17:58:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680808</loc>
  <lastmod>2026-04-18T17:57:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パッチベースの画像インペインティング（Patch-Based Image Inpainting with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-04-18T17:57:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680806</loc>
  <lastmod>2026-04-18T17:57:16Z</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>2026-04-18T17:57:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680804</loc>
  <lastmod>2026-04-18T17:57:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VANDELSサーベイが切り拓いた高赤方偏移銀河の深度分光学（The VANDELS spectroscopic survey）</news:title>
   <news:publication_date>2026-04-18T17:57:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680802</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>距離志向カーマンフィルタ粒子群最適化法（Distance-Oriented Kalman Filter Particle Swarm Optimizer）</news:title>
   <news:publication_date>2026-04-18T17:56:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/680800</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>2026-04-18T17:05:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680798</loc>
  <lastmod>2026-04-18T17:05:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-18T17:05:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680796</loc>
  <lastmod>2026-04-18T17:05:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-18T17:05:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680794</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>部分サンプリングで加速するFrank–Wolfe法の実用性（Frank-Wolfe with Subsampling Oracle）</news:title>
   <news:publication_date>2026-04-18T17:04:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680792</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>スポンサー広告ランキング最適化の深層強化学習（Optimizing Sponsored Search Ranking Strategy by Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-18T17:03:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680790</loc>
  <lastmod>2026-04-18T17:03:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層畳み込み特徴の適応共重み付けによる物体検索の改良（Adaptive Co-Weighting Deep Convolutional Features for Object Retrieval）</news:title>
   <news:publication_date>2026-04-18T17:03:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680788</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化・機械学習・高性能計算による材料開発の高速化（Accelerating Materials Development via Automation, Machine Learning, and High-Performance Computing）</news:title>
   <news:publication_date>2026-04-18T17:03:22Z</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>2026-04-18T16:11:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/680784</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>組織学画像の自動分割と線維化同定を実現する軽量CNN（Segmentation of histological images and fibrosis identification with a convolutional neural network）</news:title>
   <news:publication_date>2026-04-18T16:11:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680782</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>グラフ学習におけるゲート付き注意機構の提案（GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs）</news:title>
   <news:publication_date>2026-04-18T16:11:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680780</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>2026-04-18T16:09:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680778</loc>
  <lastmod>2026-04-18T16:09:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習における交絡因子除去が医療予測を改善する仕組み（Removing Confounding Factors Associated Weights in Deep Neural Networks Improves the Prediction Accuracy for Healthcare Applications）</news:title>
   <news:publication_date>2026-04-18T16:09:32Z</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>2026-04-18T16:09:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680774</loc>
  <lastmod>2026-04-18T16:08:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Flex-Convolutionによる百万規模点群学習（Flex-Convolution Million-Scale Point-Cloud Learning Beyond Grid-Worlds）</news:title>
   <news:publication_date>2026-04-18T16:08:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680772</loc>
  <lastmod>2026-04-18T15:17:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模合成コーパス eSCAPE（eSCAPE: a Large-scale Synthetic Corpus for Automatic Post-Editing）</news:title>
   <news:publication_date>2026-04-18T15:17:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680770</loc>
  <lastmod>2026-04-18T15:16:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的メモリネットワークによる物体追跡の学習（Learning Dynamic Memory Networks for Object Tracking）</news:title>
   <news:publication_date>2026-04-18T15:16:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680768</loc>
  <lastmod>2026-04-18T15:15:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移学習で顔の美的評価を予測する手法の解説（Transferring Rich Deep Features for Facial Beauty Prediction）</news:title>
   <news:publication_date>2026-04-18T15:15:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680766</loc>
  <lastmod>2026-04-18T15:15:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UAV群の協調学習によるフィールドカバレッジ最適化（Cooperative and Distributed Reinforcement Learning of Drones for Field Coverage）</news:title>
   <news:publication_date>2026-04-18T15:15:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680764</loc>
  <lastmod>2026-04-18T15:15:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二相流シミュレーション手法の比較：DIとVOFの実務的選択（Comparison between the diffuse interface and volume of fluid methods for simulating two-phase flows）</news:title>
   <news:publication_date>2026-04-18T15:15:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680762</loc>
  <lastmod>2026-04-18T15:15:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>疎性を持つ縮約ランク回帰と非凸正則化（Sparse Reduced Rank Regression With Nonconvex Regularization）</news:title>
   <news:publication_date>2026-04-18T15:15:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680760</loc>
  <lastmod>2026-04-18T15:14:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行動依存の因子化ベースラインによる政策勾配の分散削減（VARIANCE REDUCTION FOR POLICY GRADIENT WITH ACTION-DEPENDENT FACTORIZED BASELINES）</news:title>
   <news:publication_date>2026-04-18T15:14:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680758</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>階層的計量学習とマッチングによる2D/3D幾何対応（Hierarchical Metric Learning and Matching for 2D and 3D Geometric Correspondences）</news:title>
   <news:publication_date>2026-04-18T14:22:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680756</loc>
  <lastmod>2026-04-18T14:22:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械的プログラミングの三本柱（The Three Pillars of Machine Programming）</news:title>
   <news:publication_date>2026-04-18T14:22:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680754</loc>
  <lastmod>2026-04-18T14:22:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スライド検査の自動品質評価を実務に活かす（SlideNet: Fast and Accurate Slide Quality Assessment Based on Deep Neural Networks）</news:title>
   <news:publication_date>2026-04-18T14:22:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680752</loc>
  <lastmod>2026-04-18T14:22:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cu/Sn/Cu微小接合における界面相成長と空孔進化の解明（On the Interfacial Phase Growth and Vacancy Evolution during Accelerated Electromigration in Cu/Sn/Cu Microjoints）</news:title>
   <news:publication_date>2026-04-18T14:22:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680750</loc>
  <lastmod>2026-04-18T14:22:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>赤外線画像の多視点ATRにおける協調スパース事前分布（COLLABORATIVE SPARSE PRIORS FOR INFRARED IMAGE MULTI-VIEW ATR）</news:title>
   <news:publication_date>2026-04-18T14:22:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680748</loc>
  <lastmod>2026-04-18T14:21:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>オブジェクトの階層的な部分を学ぶ深い非滑らか非負行列因子分解（Learning the Hierarchical Parts of Objects by Deep Non-Smooth Nonnegative Matrix Factorization）</news:title>
   <news:publication_date>2026-04-18T14:21:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-04-18T14:21:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>モンテカルロ情報幾何学（Monte Carlo Information Geometry: The dually flat case）</news:title>
   <news:publication_date>2026-04-18T14:21:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>時間情報を取り入れたフレーム補完ネットワーク（A Temporally-Aware Interpolation Network for Video Frame Inpainting）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-18T13:30:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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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>2026-04-18T13:29:22Z</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>2026-04-18T13:29:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/680732</loc>
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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>2026-04-18T13:28:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/680730</loc>
  <lastmod>2026-04-18T12:37:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>フィボナッチ数を計算する十二の手法（Twelve Simple Algorithms to Compute Fibonacci Numbers）</news:title>
   <news:publication_date>2026-04-18T12:37:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/680728</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意重み付き時系列畳み込みニューラルネットワークによる行動認識の実装と示唆（Attention-based Temporal Weighted Convolutional Neural Network for Action Recognition）</news:title>
   <news:publication_date>2026-04-18T12:37:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680726</loc>
  <lastmod>2026-04-18T12:37:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>肺結節の診断分類を変えた3Dニューラルネットワーク（DIAGNOSTIC CLASSIFICATION OF LUNG NODULES USING 3D NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-04-18T12:37:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680724</loc>
  <lastmod>2026-04-18T12:35:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>非常に大きな高赤方偏移銀河の発見とその示唆（Discovery of a Very Large Galaxy at z = 3.72）</news:title>
   <news:publication_date>2026-04-18T12:35:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/680722</loc>
  <lastmod>2026-04-18T12:35:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>逆行列的GMMを敵対的に学習する手法（Adversarial Generalized Method of Moments）</news:title>
   <news:publication_date>2026-04-18T12:35:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680720</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>希少イベントに報いる自動カリキュラム学習（Automated Curriculum Learning by Rewarding Temporally Rare Events）</news:title>
   <news:publication_date>2026-04-18T12:35:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680718</loc>
  <lastmod>2026-04-18T12:35:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レンジベースのボラティリティ推定値の予測可能性とRNNによる解析（Exploring the predictability of range-based volatility estimators using RNNs）</news:title>
   <news:publication_date>2026-04-18T12:35:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/680716</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>Box-Cox ガウス過程による非ガウス時系列学習（Learning non-Gaussian Time Series using the Box-Cox Gaussian Process）</news:title>
   <news:publication_date>2026-04-18T11:42:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-18T11:33:26Z</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>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-18T11:33:10Z</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>2026-04-18T11:32:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>バッチ型量子状態指数化と量子ヘッブ学習（Batched quantum state exponentiation and quantum Hebbian learning）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドローンと深層学習で現場映像を即時解析する（Live Target Detection with Deep Learning Neural Network and Unmanned Aerial Vehicle on Android Mobile Device）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680680</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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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>要素分解型空間表現学習と心筋半教師ありセグメンテーションへの応用 (Factorised spatial representation learning: application in semi-supervised myocardial segmentation)</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680676</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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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:publication_date>2026-04-18T08:52:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680668</loc>
  <lastmod>2026-04-18T08:51:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習はいつ失敗するか（When Does Machine Learning FAIL? Generalized Transferability for Evasion and Poisoning Attacks）</news:title>
   <news:publication_date>2026-04-18T08:51:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680666</loc>
  <lastmod>2026-04-18T08:50:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>速度場のスロープ制限を用いた発散ゼロの不連続Galerkin二相流ソルバー（Slope limiting the velocity field in a discontinuous Galerkin divergence free two-phase flow solver）</news:title>
   <news:publication_date>2026-04-18T08:50:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680664</loc>
  <lastmod>2026-04-18T08:50:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Doubling Trick が多腕バンディットにもたらすものと限界（What Doubling Tricks Can and Can’t Do for Multi-Armed Bandits）</news:title>
   <news:publication_date>2026-04-18T08:50:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680662</loc>
  <lastmod>2026-04-18T08:50:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークの学習ダイナミクスとガラス物質系の比較（Comparing Dynamics: Deep Neural Networks versus Glassy Systems）</news:title>
   <news:publication_date>2026-04-18T08:50:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680660</loc>
  <lastmod>2026-04-18T07:58:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポリグロットセマンティックパーシングによるAPI翻訳（Polyglot Semantic Parsing in APIs）</news:title>
   <news:publication_date>2026-04-18T07:58:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680658</loc>
  <lastmod>2026-04-18T07:48:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴量を作らずに行動認識を学ぶ（FEATURELESS: BYPASSING FEATURE EXTRACTION IN ACTION CATEGORIZATION）</news:title>
   <news:publication_date>2026-04-18T07:48:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680656</loc>
  <lastmod>2026-04-18T07:48:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元ロジスティック回帰のための現代的最尤理論（A Modern Maximum-Likelihood Theory for High-dimensional Logistic Regression）</news:title>
   <news:publication_date>2026-04-18T07:48:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680654</loc>
  <lastmod>2026-04-18T07:47:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>hs-to-coqを用いた実運用Haskellコードの検証（Ready, Set, Verify! Applying hs-to-coq to real-world Haskell code）</news:title>
   <news:publication_date>2026-04-18T07:47:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680652</loc>
  <lastmod>2026-04-18T07:47:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一方向の重要性と汎化性能（On the Importance of Single Directions for Generalization）</news:title>
   <news:publication_date>2026-04-18T07:47:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680650</loc>
  <lastmod>2026-04-18T07:47:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>静止画像における動き予測（D´ej`a Vu: Motion Prediction in Static Images）</news:title>
   <news:publication_date>2026-04-18T07:47:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680648</loc>
  <lastmod>2026-04-18T07:46:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程における非対称カーネルによるターゲット分散学習（Asymmetric kernel in Gaussian Processes for learning target variance）</news:title>
   <news:publication_date>2026-04-18T07:46:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680646</loc>
  <lastmod>2026-04-18T06:55:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>放射線損傷シリコンにおける点欠陥とクラスタ欠陥の研究 (Study of point- and cluster-defects in radiation-damaged silicon)</news:title>
   <news:publication_date>2026-04-18T06:55:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680644</loc>
  <lastmod>2026-04-18T06:54:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PyGOMによる常微分方程式モデルの実務的簡素化（PyGOM — A Python Package for Simplifying Modelling with Systems of Ordinary Differential Equations）</news:title>
   <news:publication_date>2026-04-18T06:54:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680642</loc>
  <lastmod>2026-04-18T06:54:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>価格形成の普遍性を示す深層学習の視点（Universal features of price formation in financial markets: perspectives from Deep Learning）</news:title>
   <news:publication_date>2026-04-18T06:54:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680640</loc>
  <lastmod>2026-04-18T06:53:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数視点混合ネットワークによる乳房微細石灰化の分類（A Mixture of Views Network with Applications to the Classification of Breast Microcalcifications）</news:title>
   <news:publication_date>2026-04-18T06:53:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680638</loc>
  <lastmod>2026-04-18T06:53:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空撮画像から車線だけを正確に抜き出す技術の衝撃（Aerial LaneNet: Lane Marking Semantic Segmentation in Aerial Imagery using Wavelet-Enhanced Cost-sensitive Symmetric Fully Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-04-18T06:53:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680636</loc>
  <lastmod>2026-04-18T06:52:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味的ローカリティを用いたニューラルネットワークメモリプリフェッチ (A neural network memory prefetcher using semantic locality)</news:title>
   <news:publication_date>2026-04-18T06:52:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680634</loc>
  <lastmod>2026-04-18T06:52:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なしセマンティック深層ハッシュ（UNSUPERVISED SEMANTIC DEEP HASHING）</news:title>
   <news:publication_date>2026-04-18T06:52:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680632</loc>
  <lastmod>2026-04-18T06:01:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム演算子のスペクトル多重度と局所統計の結びつき（Global multiplicity bounds and Spectral Statistics for Random Operators）</news:title>
   <news:publication_date>2026-04-18T06:01:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680630</loc>
  <lastmod>2026-04-18T06:01:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生物学的活性化関数による深層学習の改善（Deep learning improved by biological activation functions）</news:title>
   <news:publication_date>2026-04-18T06:01:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680628</loc>
  <lastmod>2026-04-18T06:00:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元線形モデルにおける交絡因子検出（Confounder Detection in High Dimensional Linear Models using First Moments of Spectral Measures）</news:title>
   <news:publication_date>2026-04-18T06:00:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680626</loc>
  <lastmod>2026-04-18T05:59:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散認知無線ネットワークにおけるジャミング下での協調学習（Learning to Coordinate in a Decentralized Cognitive Radio Network in Presence of Jammers）</news:title>
   <news:publication_date>2026-04-18T05:59:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680624</loc>
  <lastmod>2026-04-18T05:59:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声の表現学習における異ドメイン構音データ活用（ACOUSTIC FEATURE LEARNING USING CROSS-DOMAIN ARTICULATORY MEASUREMENTS）</news:title>
   <news:publication_date>2026-04-18T05:59:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680622</loc>
  <lastmod>2026-04-18T05:59:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習可能な画像暗号化（Learnable Image Encryption）</news:title>
   <news:publication_date>2026-04-18T05:59:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680620</loc>
  <lastmod>2026-04-18T05:59:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音楽スタイル変換の位置づけと課題（Music Style Transfer: A Position Paper）</news:title>
   <news:publication_date>2026-04-18T05:59:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680618</loc>
  <lastmod>2026-04-18T05:06:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートフォンデータから行動ルールを抽出する方法（Mining User Behavioral Rules from Smartphone Data through Association Analysis）</news:title>
   <news:publication_date>2026-04-18T05:06:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680616</loc>
  <lastmod>2026-04-18T05:06:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Attention-GANによる野生画像での物体変換（Attention-GAN for Object Transfiguration in Wild Images）</news:title>
   <news:publication_date>2026-04-18T05:06:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680614</loc>
  <lastmod>2026-04-18T05:05:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Faster R-CNNの分類力を目覚めさせる（Revisiting RCNN: On Awakening the Classification Power of Faster RCNN）</news:title>
   <news:publication_date>2026-04-18T05:05:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680612</loc>
  <lastmod>2026-04-18T05:04:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボット操作のための合成可能な深層強化学習（Composable Deep Reinforcement Learning for Robotic Manipulation）</news:title>
   <news:publication_date>2026-04-18T05:04:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680610</loc>
  <lastmod>2026-04-18T05:04:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル感情分析の基礎とベンチマーク構築（Multimodal Sentiment Analysis: Addressing Key Issues and Setting up the Baselines）</news:title>
   <news:publication_date>2026-04-18T05:04:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680608</loc>
  <lastmod>2026-04-18T05:04:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TOMAAT: 体積医用画像解析のクラウドサービス化（TOMAAT: volumetric medical image analysis as a cloud service）</news:title>
   <news:publication_date>2026-04-18T05:04:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680606</loc>
  <lastmod>2026-04-18T05:04:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非局所低ランクテンソル因子解析による画像復元（Nonlocal Low-Rank Tensor Factor Analysis for Image Restoration）</news:title>
   <news:publication_date>2026-04-18T05:04:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680604</loc>
  <lastmod>2026-04-18T04:11:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトウェア定義ネットワーク向けの効率的な異常検知法（Towards an Efficient Anomaly-Based Intrusion Detection for Software-Defined Networks）</news:title>
   <news:publication_date>2026-04-18T04:11:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680602</loc>
  <lastmod>2026-04-18T04:11:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EnvelopeNetsによる高速ニューラルアーキテクチャ構築（Fast Neural Architecture Construction using EnvelopeNets）</news:title>
   <news:publication_date>2026-04-18T04:11:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680600</loc>
  <lastmod>2026-04-18T04:11:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>密集フェムトセル環境におけるQoSを考慮した出力割当の機械学習的アプローチ（A Machine Learning Approach for Power Allocation in HetNets Considering QoS）</news:title>
   <news:publication_date>2026-04-18T04:11:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680598</loc>
  <lastmod>2026-04-18T04:10:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワンビット通信で分散検出を実現する（Detection under One-Bit Messaging over Adaptive Networks）</news:title>
   <news:publication_date>2026-04-18T04:10:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680596</loc>
  <lastmod>2026-04-18T04:09:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模動的予測回帰の分解・再結合戦略（Large-Scale Dynamic Predictive Regressions）</news:title>
   <news:publication_date>2026-04-18T04:09:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680594</loc>
  <lastmod>2026-04-18T04:09:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期予測のための集約戦略（Aggregating Strategies for Long-term Forecasting）</news:title>
   <news:publication_date>2026-04-18T04:09:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680592</loc>
  <lastmod>2026-04-18T04:09:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚と意味を同時に識別可能にするゼロショット学習（Discriminative Learning of Latent Features for Zero-Shot Recognition）</news:title>
   <news:publication_date>2026-04-18T04:09:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680590</loc>
  <lastmod>2026-04-18T03:17:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プログラムを言葉にして学ぶ――抽象化された象徴的トレースからのコードベクトル（Code Vectors: Understanding Programs Through Embedded Abstracted Symbolic Traces）</news:title>
   <news:publication_date>2026-04-18T03:17:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680588</loc>
  <lastmod>2026-04-18T03:17:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>格子基底縮約を用いた高次元線形回帰（High Dimensional Linear Regression using Lattice Basis Reduction）</news:title>
   <news:publication_date>2026-04-18T03:17:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680586</loc>
  <lastmod>2026-04-18T03:17:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>監督学習によるスキルミオン相認識の実用的意義（Supervised-learning approach for recognizing magnetic skyrmion phases）</news:title>
   <news:publication_date>2026-04-18T03:17:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680584</loc>
  <lastmod>2026-04-18T03:16:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異なる深度マップを賢く融合する半教師ありマルチスケール敵対ネットワーク（SDF-MAN: SEMI-SUPERVISED DISPARITY FUSION WITH MULTI-SCALE ADVERSARIAL NETWORKS）</news:title>
   <news:publication_date>2026-04-18T03:16:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680582</loc>
  <lastmod>2026-04-18T03:15:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン鎖分割とスケジューリング（On-line Chain Partitioning Approach to Scheduling）</news:title>
   <news:publication_date>2026-04-18T03:15:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680580</loc>
  <lastmod>2026-04-18T03:15:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>三峡ダム流域の土地利用マッピング（Land use mapping in the Three Gorges Reservoir Area based on semantic segmentation deep learning method）</news:title>
   <news:publication_date>2026-04-18T03:15:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680578</loc>
  <lastmod>2026-04-18T03:15:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元データにおける希少特徴選択の再考（Rare Feature Selection in High Dimensions）</news:title>
   <news:publication_date>2026-04-18T03:15:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680576</loc>
  <lastmod>2026-04-18T02:23:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LINE ARTIST：マルチスタイル スケッチから絵画生成スキーム（LINE ARTIST: A Multi-style Sketch to Painting Synthesis Scheme）</news:title>
   <news:publication_date>2026-04-18T02:23:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680574</loc>
  <lastmod>2026-04-18T02:23:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェブを知識ベースとして複雑な質問に答える方法（The Web as a Knowledge-base for Answering Complex Questions）</news:title>
   <news:publication_date>2026-04-18T02:23:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680572</loc>
  <lastmod>2026-04-18T02:22:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Zoom and Learn: 新領域に適応する深層ステレオマッチング（Zoom and Learn: Generalizing Deep Stereo Matching to Novel Domains）</news:title>
   <news:publication_date>2026-04-18T02:22:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680570</loc>
  <lastmod>2026-04-18T02:21:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生態写真から蝶を自動検出・種同定する技術の実務的意義（Faster R-CNN based butterfly automatic identification）</news:title>
   <news:publication_date>2026-04-18T02:21:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680568</loc>
  <lastmod>2026-04-18T02:21:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エントロピー最小化による適応的意思決定（Adaptive Decision Making via Entropy Minimization）</news:title>
   <news:publication_date>2026-04-18T02:21:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680566</loc>
  <lastmod>2026-04-18T02:21:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DAMPEデータを用いた電子・陽子分離の機械学習手法（A machine learning method to separate cosmic ray electrons from protons from 10 to 100 GeV using DAMPE data）</news:title>
   <news:publication_date>2026-04-18T02:21:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680564</loc>
  <lastmod>2026-04-18T02:21:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半触覚インターフェースによる楽器学習の再定義（ShIFT: A Semi-haptic Interface for Flute Tutoring）</news:title>
   <news:publication_date>2026-04-18T02:21:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680562</loc>
  <lastmod>2026-04-18T01:29:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>盲目的量子計算は常に検証可能にできる（Blind quantum computing can always be made verifiable）</news:title>
   <news:publication_date>2026-04-18T01:29:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680560</loc>
  <lastmod>2026-04-18T01:29:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習によるスパイキングネットワークの反復動態（Learning recurrent dynamics in spiking networks）</news:title>
   <news:publication_date>2026-04-18T01:29:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680558</loc>
  <lastmod>2026-04-18T01:28:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大学卒業後の収入を決める特徴量の選択（Feature Selection of Post-Graduation Income of College Students in the United States）</news:title>
   <news:publication_date>2026-04-18T01:28:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680556</loc>
  <lastmod>2026-04-18T01:27:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>陽性と未ラベルの分類で頑健なAUC最大化と外れ値検出・特徴選択の統合（A Robust AUC Maximization Framework with Simultaneous Outlier Detection and Feature Selection for Positive-Unlabeled Classification）</news:title>
   <news:publication_date>2026-04-18T01:27:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680554</loc>
  <lastmod>2026-04-18T01:26:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軌跡に基づくシーン理解と非パラメトリック混合モデル（Trajectory-based Scene Understanding using Dirichlet Process Mixture Model）</news:title>
   <news:publication_date>2026-04-18T01:26:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680552</loc>
  <lastmod>2026-04-18T01:26:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己反復回帰による顔ランドマーク検出とランドマーク注意ネットワーク（Facial Landmarks Detection by Self-Iterative Regression based Landmarks-Attention Network）</news:title>
   <news:publication_date>2026-04-18T01:26:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680550</loc>
  <lastmod>2026-04-18T01:25:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報理論的セキュリティと隠密通信（Information-Theoretic Security or Covert Communication）</news:title>
   <news:publication_date>2026-04-18T01:25:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680547</loc>
  <lastmod>2026-04-18T00:33:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造的Query‑by‑Committeeの統一的枠組み（Structural query-by-committee）</news:title>
   <news:publication_date>2026-04-18T00:33:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680545</loc>
  <lastmod>2026-04-18T00:33:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多重散乱の高速かつ高精度な反転を行う深層学習（Efficient and accurate inversion of multiple scattering with deep learning）</news:title>
   <news:publication_date>2026-04-18T00:33:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680543</loc>
  <lastmod>2026-04-18T00:33:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集中治療室における早期院内死亡予測（Early Hospital Mortality Prediction using Vital Signals）</news:title>
   <news:publication_date>2026-04-18T00:33:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680541</loc>
  <lastmod>2026-04-18T00:32:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークのスケーラブル検証に向けた二重アプローチ（A Dual Approach to Scalable Verification of Deep Networks）</news:title>
   <news:publication_date>2026-04-18T00:32:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680539</loc>
  <lastmod>2026-04-18T00:32:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限時間スループット最大化とセンシング最適化（Finite Horizon Throughput Maximization and Sensing Optimization in Wireless Powered Devices over Fading Channels）</news:title>
   <news:publication_date>2026-04-18T00:32:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680537</loc>
  <lastmod>2026-04-18T00:32:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サービス提供者視点のAutoML：多デバイス・多テナント下でのGP‑EIによるモデル選択（AutoML from Service Provider’s Perspective: Multi-device, Multi-tenant Model Selection with GP-EI）</news:title>
   <news:publication_date>2026-04-18T00:32:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680535</loc>
  <lastmod>2026-04-18T00:31:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期依存性学習のためのフーリエ回帰ユニット（Learning Long Term Dependencies via Fourier Recurrent Units）</news:title>
   <news:publication_date>2026-04-18T00:31:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680533</loc>
  <lastmod>2026-04-17T23:39:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>なぜそうなのかを教えてください？知識グラフ関係の説明文抽出（Tell Me Why Is It So? Explaining Knowledge Graph Relationships by Finding Descriptive Support Passages）</news:title>
   <news:publication_date>2026-04-17T23:39:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680531</loc>
  <lastmod>2026-04-17T23:39:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アクティブラーニングで脆弱性検査を効率化する発想（Improving Vulnerability Inspection Efficiency Using Active Learning）</news:title>
   <news:publication_date>2026-04-17T23:39:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680529</loc>
  <lastmod>2026-04-17T23:39:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多相配電網におけるトポロジー推定（Topology Estimation using Graphical Models in Multi-Phase Power Distribution Grids）</news:title>
   <news:publication_date>2026-04-17T23:39:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680527</loc>
  <lastmod>2026-04-17T23:38:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブキューブ混合モデルの学習を高速化する理論的進展（Beyond the Low-Degree Algorithm: Mixtures of Subcubes and Their Applications）</news:title>
   <news:publication_date>2026-04-17T23:38:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680525</loc>
  <lastmod>2026-04-17T23:38:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生物シグナルネットワークにおける三頂点モチーフが示す微細トポロジーと機能の関係 (Analysis of Triplet Motifs in Biological Signed Oriented Graphs Suggests a Relationship Between Fine Topology and Function)</news:title>
   <news:publication_date>2026-04-17T23:38:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680523</loc>
  <lastmod>2026-04-17T23:38:13Z</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>2026-04-17T23:38:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680521</loc>
  <lastmod>2026-04-17T23:38:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SeqFace: 連続情報を活用した顔認識（SeqFace: Make full use of sequence information for face recognition）</news:title>
   <news:publication_date>2026-04-17T23:38:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680519</loc>
  <lastmod>2026-04-17T22:46:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソルの凸ココクラスタリングによる可証的分割法（Provable Convex Co-clustering of Tensors）</news:title>
   <news:publication_date>2026-04-17T22:46:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680517</loc>
  <lastmod>2026-04-17T22:46:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SDP緩和の隠れた積分性と半ランダム堅牢性（Hidden Integrality and Semi-random Robustness of SDP Relaxation for Sub-Gaussian Mixture Model）</news:title>
   <news:publication_date>2026-04-17T22:46:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680515</loc>
  <lastmod>2026-04-17T22:45:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MergeNetによる小さな路上障害物検出の革新（MergeNet: A Deep Net Architecture for Small Obstacle Discovery）</news:title>
   <news:publication_date>2026-04-17T22:45:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680513</loc>
  <lastmod>2026-04-17T22:45:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>概念学習による無監督視覚グラウンディングの学習（Learning Unsupervised Visual Grounding Through Semantic Self-Supervision）</news:title>
   <news:publication_date>2026-04-17T22:45:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680511</loc>
  <lastmod>2026-04-17T22:45:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イベントベース視覚データのロバスト追跡（Robust event-stream pattern tracking based on correlative filter）</news:title>
   <news:publication_date>2026-04-17T22:45:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680509</loc>
  <lastmod>2026-04-17T22:44:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変長粒子群最適化による深層畳み込みニューラルネットワークの進化（Evolving Deep Convolutional Neural Networks by Variable-length Particle Swarm Optimization for Image Classification）</news:title>
   <news:publication_date>2026-04-17T22:44:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680507</loc>
  <lastmod>2026-04-17T22:44:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像ラベルのみで注目領域を検出する弱教師あり手法（Weakly Supervised Salient Object Detection Using Image Labels）</news:title>
   <news:publication_date>2026-04-17T22:44:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680505</loc>
  <lastmod>2026-04-17T21:53:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平均回帰ポートフォリオの設計と推定（Mean Reverting Portfolios via Penalized OU-Likelihood Estimation）</news:title>
   <news:publication_date>2026-04-17T21:53:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680503</loc>
  <lastmod>2026-04-17T21:53:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像解析による待ち行列理論に基づくインテリジェント交通信号スケジューリング（Queuing Theory Guided Intelligent Traffic Scheduling through Video Analysis using Dirichlet Process Mixture Model）</news:title>
   <news:publication_date>2026-04-17T21:53:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680501</loc>
  <lastmod>2026-04-17T21:53:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粗い微分方程式の解の定義について（On the definition of a solution to a rough differential equation）</news:title>
   <news:publication_date>2026-04-17T21:53:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680499</loc>
  <lastmod>2026-04-17T21:52:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小規模・大規模の著者認証に関するニューラルネットワークの実験（Experiments with Neural Networks for Small and Large Scale Authorship Verification）</news:title>
   <news:publication_date>2026-04-17T21:52:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680497</loc>
  <lastmod>2026-04-17T21:52:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在自己相関の最大化がタンパク質動力学の変分符号化に与える利点（Variational Encoding of Protein Dynamics Benefits from Maximizing Latent Autocorrelation）</news:title>
   <news:publication_date>2026-04-17T21:52:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680495</loc>
  <lastmod>2026-04-17T21:52:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピクセル単位クラスタ学習による提案不要のインスタンスセグメンテーション（Learning to Cluster for Proposal-Free Instance Segmentation）</news:title>
   <news:publication_date>2026-04-17T21:52:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680493</loc>
  <lastmod>2026-04-17T21:52:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付き深層学習と条件付き勾配法の応用（Constrained Deep Learning using Conditional Gradient and Applications in Computer Vision）</news:title>
   <news:publication_date>2026-04-17T21:52:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680491</loc>
  <lastmod>2026-04-17T21:01:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-17T21:01:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680489</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>通信圧縮と分散学習の両立で変わる分散学習の実務適用（Communication Compression for Decentralized Training）</news:title>
   <news:publication_date>2026-04-17T21:00:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680487</loc>
  <lastmod>2026-04-17T21:00:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元・モデルミススペシフィケーション下の大規模モデル選択（Large-Scale Model Selection with Misspecification）</news:title>
   <news:publication_date>2026-04-17T21:00:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680485</loc>
  <lastmod>2026-04-17T20:59:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Blaschke unwinding AFDに基づく心電図圧縮法の実用化可能性（A Novel Blaschke Unwinding Adaptive Fourier Decomposition Based Signal Compression Algorithm With Application on ECG Signals）</news:title>
   <news:publication_date>2026-04-17T20:59:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680483</loc>
  <lastmod>2026-04-17T20:59:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人工マイクロスイマーの強化学習による自律化（Reinforcement Learning of Artificial Microswimmers）</news:title>
   <news:publication_date>2026-04-17T20:59:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680481</loc>
  <lastmod>2026-04-17T20:59:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体インスタンスの弱教師ありセグメンテーションを切り貼りで学ぶ（Learning to Segment by Cut and Paste）</news:title>
   <news:publication_date>2026-04-17T20:59:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680479</loc>
  <lastmod>2026-04-17T20:59:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>成長するデータベースの差分プライバシー（Differential Privacy for Growing Databases）</news:title>
   <news:publication_date>2026-04-17T20:59:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680477</loc>
  <lastmod>2026-04-17T20:07:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層成分解析と交互方向ニューラルネットワーク（Deep Component Analysis via Alternating Direction Neural Networks）</news:title>
   <news:publication_date>2026-04-17T20:07:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680475</loc>
  <lastmod>2026-04-17T20:07:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意思決定支援におけるテキスト感情認識のための深層学習（Deep learning for affective computing: text-based emotion recognition in decision support）</news:title>
   <news:publication_date>2026-04-17T20:07:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680473</loc>
  <lastmod>2026-04-17T20:07:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で条件付き現金給付（CCT）政策をどう評価するか（Evaluating Conditional Cash Transfer Policies with Machine Learning Methods）</news:title>
   <news:publication_date>2026-04-17T20:07:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680471</loc>
  <lastmod>2026-04-17T20:06:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインデータのテキスト分類におけるコーパス統計（Corpus Statistics in Text Classification of Online Data）</news:title>
   <news:publication_date>2026-04-17T20:06:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680469</loc>
  <lastmod>2026-04-17T20:06:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DUNE 35トン試作検出器の光検出器システムの時間性能（Photon detector system timing performance in the DUNE 35-ton prototype）</news:title>
   <news:publication_date>2026-04-17T20:06:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680467</loc>
  <lastmod>2026-04-17T20:05:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経済・金融時系列予測：ARIMA vs. LSTM（Forecasting Economic and Financial Time Series: ARIMA vs. LSTM）</news:title>
   <news:publication_date>2026-04-17T20:05:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680465</loc>
  <lastmod>2026-04-17T20:05:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰型逆伝播の復活と改良（Reviving and Improving Recurrent Back-Propagation）</news:title>
   <news:publication_date>2026-04-17T20:05:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680463</loc>
  <lastmod>2026-04-17T19:13:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経験的ゲーム理論解析の一般化手法（A Generalised Method for Empirical Game Theoretic Analysis）</news:title>
   <news:publication_date>2026-04-17T19:13:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680461</loc>
  <lastmod>2026-04-17T19:13:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対数出力の整合で堅牢化する手法（Adversarial Logit Pairing）</news:title>
   <news:publication_date>2026-04-17T19:13:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680459</loc>
  <lastmod>2026-04-17T19:13:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル機械翻訳のためのTensor2Tensor（Tensor2Tensor for Neural Machine Translation）</news:title>
   <news:publication_date>2026-04-17T19:13:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680457</loc>
  <lastmod>2026-04-17T19:11:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セマンティック敵対的事例とその示唆（Semantic Adversarial Examples）</news:title>
   <news:publication_date>2026-04-17T19:11:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680455</loc>
  <lastmod>2026-04-17T19:11:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/680453</loc>
  <lastmod>2026-04-17T19:11:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Snap MLによる階層的機械学習フレームワークの要点解説（Snap ML: A Hierarchical Framework for Machine Learning）</news:title>
   <news:publication_date>2026-04-17T19:11:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/680451</loc>
  <lastmod>2026-04-17T19:10:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔を照明プローブとして使う（Faces as Lighting Probes via Unsupervised Deep Highlight Extraction）</news:title>
   <news:publication_date>2026-04-17T19:10:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/680449</loc>
  <lastmod>2026-04-17T18:18:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率プログラムのネスト化がもたらす統計的影響（Nesting Probabilistic Programs）</news:title>
   <news:publication_date>2026-04-17T18:18:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680447</loc>
  <lastmod>2026-04-17T18:18:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Structured Active Contoursによる建物境界の精密化（Learning deep structured active contours end-to-end）</news:title>
   <news:publication_date>2026-04-17T18:18:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/680445</loc>
  <lastmod>2026-04-17T18:18:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粒子ベースの変分的BNMFアプローチ（A particle-based variational approach to BNMF）</news:title>
   <news:publication_date>2026-04-17T18:18:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/680443</loc>
  <lastmod>2026-04-17T18:17:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EVA2によるライブコンピュータビジョンの省力化（EVA2: Exploiting Temporal Redundancy in Live Computer Vision）</news:title>
   <news:publication_date>2026-04-17T18:17:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/680441</loc>
  <lastmod>2026-04-17T18:17:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分的なマルチマッチングの同期化（Synchronisation of Partial Multi-Matchings via Non-negative Factorisations）</news:title>
   <news:publication_date>2026-04-17T18:17:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680439</loc>
  <lastmod>2026-04-17T18:16:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超拡散銀河の星成分の分光学的特徴づけ（Spectroscopic characterisation of the stellar content of ultra diffuse galaxies）</news:title>
   <news:publication_date>2026-04-17T18:16:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680437</loc>
  <lastmod>2026-04-17T18:16:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成画像の現実性最適化によるパーツ分割性能の改善（Improved Part Segmentation Performance by Optimising Realism of Synthetic Images using Cycle Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-04-17T18:16:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680435</loc>
  <lastmod>2026-04-17T17:24:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元確率反転に対する随伴モデルと機械学習の統合（High-dimensional Stochastic Inversion via Adjoint Models and Machine Learning）</news:title>
   <news:publication_date>2026-04-17T17:24:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680433</loc>
  <lastmod>2026-04-17T17:24:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二層最適化によるハイブリッドシステムの反証探索（Two-Layered Falsification of Hybrid Systems Guided by Monte Carlo Tree Search）</news:title>
   <news:publication_date>2026-04-17T17:24:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680431</loc>
  <lastmod>2026-04-17T17:24:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ分割ニューラルネットワークによる半教師付き分類（Graph Partition Neural Networks for Semi-Supervised Classification）</news:title>
   <news:publication_date>2026-04-17T17:24:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680429</loc>
  <lastmod>2026-04-17T17:22:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手書き文書におけるテキストと固有表現の同時認識（Joint Recognition of Handwritten Text and Named Entities with a Neural End-to-end Model）</news:title>
   <news:publication_date>2026-04-17T17:22:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680427</loc>
  <lastmod>2026-04-17T17:22:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シオンガン新区における将来都市成長のシミュレーション（Simulating the future urban growth in Xiongan New Area: a upcoming big city in China）</news:title>
   <news:publication_date>2026-04-17T17:22:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680425</loc>
  <lastmod>2026-04-17T17:22:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回転等変性を組み込んだ高解像度土地被覆マッピング（Land cover mapping at very high resolution with rotation equivariant CNNs）</news:title>
   <news:publication_date>2026-04-17T17:22:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680423</loc>
  <lastmod>2026-04-17T17:22:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共有施設利用者の調整をデータ駆動予測で支援する（Coordinating users of shared facilities via data-driven predictive assistants and game theory）</news:title>
   <news:publication_date>2026-04-17T17:22:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680421</loc>
  <lastmod>2026-04-17T16:30:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチビュー3D物体検索に効くトリプレットセンター損失（Triplet-Center Loss for Multi-View 3D Object Retrieval）</news:title>
   <news:publication_date>2026-04-17T16:30:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680419</loc>
  <lastmod>2026-04-17T16:22:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子グラフ畳み込みによる薬物物性予測の新展開（Chemi-Net: A molecular graph convolutional network for accurate drug property prediction）</news:title>
   <news:publication_date>2026-04-17T16:22:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680417</loc>
  <lastmod>2026-04-17T16:22:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協力と競争で重みを決める発電予測アンサンブル（A Multi-Scheme Ensemble Using Coopetitive Soft-Gating With Application to Power Forecasting for Renewable Energy Generation）</news:title>
   <news:publication_date>2026-04-17T16:22:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680415</loc>
  <lastmod>2026-04-17T16:21:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔写真ベースの年齢推定データベースの公開がもたらすインパクト（The AgeGuess database: an open online resource on chronological and perceived ages of people aged 3-100）</news:title>
   <news:publication_date>2026-04-17T16:21:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680413</loc>
  <lastmod>2026-04-17T16:20:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UVITによるラム圧剥離の観測：Abell 85のGASPジェリーフィッシュ銀河JO201の剥離ガスにおける星形成（UVIT view of ram-pressure stripping in action: Star formation in the stripped gas of the GASP jellyfish galaxy JO201 in Abell 85）</news:title>
   <news:publication_date>2026-04-17T16:20:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680411</loc>
  <lastmod>2026-04-17T16:20:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>第三世代クォークに結合する重いBSM粒子の探索（Search for heavy BSM particles coupling to third generation quarks at CMS）</news:title>
   <news:publication_date>2026-04-17T16:20:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680409</loc>
  <lastmod>2026-04-17T16:19:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データの信頼性応用における複雑性の次元（Big Data and Reliability Applications: The Complexity Dimension）</news:title>
   <news:publication_date>2026-04-17T16:19:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680407</loc>
  <lastmod>2026-04-17T15:27:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ApolloScapeによる自動運転用大規模データセットの価値（The ApolloScape Open Dataset for Autonomous Driving and its Application）</news:title>
   <news:publication_date>2026-04-17T15:27:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680405</loc>
  <lastmod>2026-04-17T15:27:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ARMスケーラブルベクター拡張（The ARM Scalable Vector Extension）</news:title>
   <news:publication_date>2026-04-17T15:27:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680403</loc>
  <lastmod>2026-04-17T15:27:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GDPR時代におけるHCIの優先課題（Some HCI Priorities for GDPR-Compliant Machine Learning）</news:title>
   <news:publication_date>2026-04-17T15:27:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680401</loc>
  <lastmod>2026-04-17T15:26:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>巨大星周囲の塵円盤に見つかった偏光の意味（A polarized dusty disk around a massive star）</news:title>
   <news:publication_date>2026-04-17T15:26:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680399</loc>
  <lastmod>2026-04-17T15:25:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体の言語記述による検出と検索の統合（Object Captioning and Retrieval with Natural Language）</news:title>
   <news:publication_date>2026-04-17T15:25:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680397</loc>
  <lastmod>2026-04-17T15:25:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エネルギー自律型モバイルネットワークの実現（Energy Sustainable Mobile Networks via Energy Routing, Learning and Foresighted Optimization）</news:title>
   <news:publication_date>2026-04-17T15:25:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/680395</loc>
  <lastmod>2026-04-17T15:25:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>間質性肺疾患の病理組織セグメンテーション（Semantic Segmentation of Pathological Lung Tissue with Dilated Fully Convolutional Networks）</news:title>
   <news:publication_date>2026-04-17T15:25:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
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