<?xml version="1.0" encoding="UTF-8"?>
<!--generator='jetpack-16.2-a.3'-->
<!--Jetpack_Sitemap_Buffer_News_XMLWriter-->
<?xml-stylesheet type="text/xsl" href="//aibr.jp/news-sitemap.xsl"?>
<urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9" xmlns:news="http://www.google.com/schemas/sitemap-news/0.9" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.sitemaps.org/schemas/sitemap/0.9 http://www.sitemaps.org/schemas/sitemap/0.9/sitemap.xsd">
 <url>
  <loc>https://aibr.jp/archives/728229</loc>
  <lastmod>2026-08-28T14:34:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型経済的NMPCによる強化学習の統合（Data-driven Economic NMPC using Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-28T14:34:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728227</loc>
  <lastmod>2026-08-28T14:33:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンタリオ州の集団保健データを用いた糖尿病発症予測（Diabetes Mellitus Forecasting Using Population Health Data in Ontario, Canada）</news:title>
   <news:publication_date>2026-08-28T14:33:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728225</loc>
  <lastmod>2026-08-28T14:32:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼画像からの深度推定にステレオ知識を注入する手法（Learning monocular depth estimation infusing traditional stereo knowledge）</news:title>
   <news:publication_date>2026-08-28T14:32:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728223</loc>
  <lastmod>2026-08-28T14:32:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EoRパラメータ再構築のための改良された教師あり学習法 (Improved supervised learning methods for EoR parameters reconstruction)</news:title>
   <news:publication_date>2026-08-28T14:32:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728221</loc>
  <lastmod>2026-08-28T14:31:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化された構造探索と漸進的絞込みで効率化するNAS（ASAP: Architecture Search, Anneal and Prune）</news:title>
   <news:publication_date>2026-08-28T14:31:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728219</loc>
  <lastmod>2026-08-28T14:31:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>完全無監督の音声認識をGANとHMMで実現する枠組み（Completely Unsupervised Speech Recognition By A Generative Adversarial Network Harmonized With Iteratively Refined Hidden Markov Models）</news:title>
   <news:publication_date>2026-08-28T14:31:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728217</loc>
  <lastmod>2026-08-28T14:31:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワーク学習のための加重点群増強（Weighted Point Cloud Augmentation for Neural Network Training）</news:title>
   <news:publication_date>2026-08-28T14:31:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728215</loc>
  <lastmod>2026-08-28T13:39:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成型ゼロショット学習における不変側面の活用（Leveraging the Invariant Side of Generative Zero-Shot Learning）</news:title>
   <news:publication_date>2026-08-28T13:39:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728213</loc>
  <lastmod>2026-08-28T13:39:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大マージン多モーダル・多タスク特徴抽出による画像分類（Large Margin Multi-modal Multi-task Feature Extraction for Image Classification）</news:title>
   <news:publication_date>2026-08-28T13:39:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728211</loc>
  <lastmod>2026-08-28T13:38:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローカル記述子の文脈拡張による精度向上（Local Descriptor Augmentation with Cross-Modality Context）</news:title>
   <news:publication_date>2026-08-28T13:38:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728209</loc>
  <lastmod>2026-08-28T13:38:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種ドメインからの知識断片転移による距離学習（Transferring Knowledge Fragments for Learning Distance Metric from A Heterogeneous Domain）</news:title>
   <news:publication_date>2026-08-28T13:38:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728207</loc>
  <lastmod>2026-08-28T13:37:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重要でない経験を弾くことで強化学習の効率を高める発想（Only Relevant Information Matters: Filtering Out Noisy Samples to Boost RL）</news:title>
   <news:publication_date>2026-08-28T13:37:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728205</loc>
  <lastmod>2026-08-28T13:37:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>核状ニューラルネットワークによる自己組織化アーキテクチャ（Nucleus Neural Network: A Data-driven Self-organized Architecture）</news:title>
   <news:publication_date>2026-08-28T13:37:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728203</loc>
  <lastmod>2026-08-28T13:37:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種マルチタスク距離学習による多領域横断（Heterogeneous Multi-task Metric Learning across Multiple Domains）</news:title>
   <news:publication_date>2026-08-28T13:37:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728201</loc>
  <lastmod>2026-08-28T12:45:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変化する密度を捉える頑健なクラスタリング手法（CRAD: Clustering with Robust Autocuts and Depth）</news:title>
   <news:publication_date>2026-08-28T12:45:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728199</loc>
  <lastmod>2026-08-28T12:44:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Jensen-Shannon発散の一般化（On a generalization of the Jensen-Shannon divergence and the JS-symmetrization of distances relying on abstract means）</news:title>
   <news:publication_date>2026-08-28T12:44:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728197</loc>
  <lastmod>2026-08-28T12:44:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集合知の浸透現象としての相互知識の出現（Coupling agent based simulation with dynamic networks analysis to study the emergence of mutual knowledge as a percolation phenomenon）</news:title>
   <news:publication_date>2026-08-28T12:44:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728195</loc>
  <lastmod>2026-08-28T12:43:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトル空間特徴の同時選択と抽出（Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images）</news:title>
   <news:publication_date>2026-08-28T12:43:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728193</loc>
  <lastmod>2026-08-28T12:43:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間行動を組み込む大気汚染シミュレーション（A Multi-Agent based Approach for Simulating the Impact of Human Behaviours on Air Pollution）</news:title>
   <news:publication_date>2026-08-28T12:43:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728191</loc>
  <lastmod>2026-08-28T12:43:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メルスペクトログラムからの音声合成を高速化するGAN励起線形予測（GELP: GAN-Excited Linear Prediction for Speech Synthesis from Mel-spectrogram）</news:title>
   <news:publication_date>2026-08-28T12:43:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728189</loc>
  <lastmod>2026-08-28T12:42:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>採卵生産曲線における早期警報の実装（Early warning in egg production curves from commercial hens: A SVM approach）</news:title>
   <news:publication_date>2026-08-28T12:42:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728187</loc>
  <lastmod>2026-08-28T11:51:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AdaBoostを特徴学習の観点で見る意義とAdaBoost+SVMの実装可能性（Feature Learning Viewpoint of AdaBoost and a New Algorithm）</news:title>
   <news:publication_date>2026-08-28T11:51:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728185</loc>
  <lastmod>2026-08-28T11:42:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン討論フォーラムにおけるイシューフレーミングの検出（Issue Framing in Online Discussion Fora）</news:title>
   <news:publication_date>2026-08-28T11:42:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728183</loc>
  <lastmod>2026-08-28T11:42:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様性と品質を同時に評価する指標の提案（Jointly Measuring Diversity and Quality in Text Generation Models）</news:title>
   <news:publication_date>2026-08-28T11:42:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728181</loc>
  <lastmod>2026-08-28T11:42:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近傍の優れたCNNへ切り替えるフィルタ剪定（Filter Pruning by Switching to Neighboring CNNs with Good Attributes）</news:title>
   <news:publication_date>2026-08-28T11:42:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728179</loc>
  <lastmod>2026-08-28T11:42:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ナノ構造化された層状材料による赤外線双曲メタサーフェス（Infrared hyperbolic metasurface based on nanostructured van der Waals materials）</news:title>
   <news:publication_date>2026-08-28T11:42:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728177</loc>
  <lastmod>2026-08-28T11:41:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像分類の頑健性を高めるフィルタ選択型ファインチューニング（Improving Image Classification Robustness through Selective CNN-Filters Fine-Tuning）</news:title>
   <news:publication_date>2026-08-28T11:41:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728175</loc>
  <lastmod>2026-08-28T11:41:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SIPAによるモデル非依存型解釈の統一的フレームワーク（Sampling, Intervention, Prediction, Aggregation: A Generalized Framework for Model-Agnostic Interpretations）</news:title>
   <news:publication_date>2026-08-28T11:41:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728173</loc>
  <lastmod>2026-08-28T10:50:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数出力予測のためのターゲット逐次ブースティング（Component-Wise Boosting of Targets for Multi-Output Prediction）</news:title>
   <news:publication_date>2026-08-28T10:50:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728171</loc>
  <lastmod>2026-08-28T10:50:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベルノイズに強い学習のためのワッサースタイン敵対的正則化（Wasserstein Adversarial Regularization for learning with label noise）</news:title>
   <news:publication_date>2026-08-28T10:50:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728169</loc>
  <lastmod>2026-08-28T10:49:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河の局所的な星形成率と金属量の関係の実証（Characterizing the local SFR − Zg relation in MaNGA spiral galaxies）</news:title>
   <news:publication_date>2026-08-28T10:49:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728167</loc>
  <lastmod>2026-08-28T10:49:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン変分推論の一般化境界（A Generalization Bound for Online Variational Inference）</news:title>
   <news:publication_date>2026-08-28T10:49:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728165</loc>
  <lastmod>2026-08-28T10:49:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文書横断の言語不変表現：縮小ランクリッジ回帰による埋め込み（Crosslingual Document Embedding as Reduced-Rank Ridge Regression）</news:title>
   <news:publication_date>2026-08-28T10:49:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728163</loc>
  <lastmod>2026-08-28T10:48:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>密度認識埋め込みの学習（On Learning Density Aware Embeddings）</news:title>
   <news:publication_date>2026-08-28T10:48:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728161</loc>
  <lastmod>2026-08-28T10:48:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチビュー・ベクトル値マニフォールド正則化によるマルチラベル画像分類（Multi-view Vector-valued Manifold Regularization for Multi-label Image Classification）</news:title>
   <news:publication_date>2026-08-28T10:48:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728159</loc>
  <lastmod>2026-08-28T09:56:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dual Question-Answer Extractionを用いた半教師あり少数ショット学習の実務的意義（Semi-Supervised Few-Shot Learning for Dual Question-Answer Extraction）</news:title>
   <news:publication_date>2026-08-28T09:56:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728157</loc>
  <lastmod>2026-08-28T09:47:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化された能動学習と統計実験設計（Generalized active learning and design of statistical experiments for manifold-valued data）</news:title>
   <news:publication_date>2026-08-28T09:47:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728155</loc>
  <lastmod>2026-08-28T09:47:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習に基づくCT再構成の現状と課題（Deep Learning Based Computed Tomography: Whys and Wherefores）</news:title>
   <news:publication_date>2026-08-28T09:47:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728153</loc>
  <lastmod>2026-08-28T09:47:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチビュー行列補完による多ラベル画像分類（Multi-View Matrix Completion for Multi-Label Image Classification）</news:title>
   <news:publication_date>2026-08-28T09:47:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728151</loc>
  <lastmod>2026-08-28T09:46:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジャミングを逆手に取る通信戦略（Jam Me If You Can: Defeating Jammer with Deep Dueling Neural Network Architecture and Ambient Backscattering Augmented Communications）</news:title>
   <news:publication_date>2026-08-28T09:46:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728149</loc>
  <lastmod>2026-08-28T09:46:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パッチから画像分割へ ― 完全畳み込みネットワークの網羅的応用（From Patch to Image Segmentation using Fully Convolutional Networks - Application to Retinal Images）</news:title>
   <news:publication_date>2026-08-28T09:46:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728147</loc>
  <lastmod>2026-08-28T09:45:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D屋内ナビゲーションのためのシム・リアル共同強化学習転移（Sim-Real Joint Reinforcement Transfer for 3D Indoor Navigation）</news:title>
   <news:publication_date>2026-08-28T09:45:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728145</loc>
  <lastmod>2026-08-28T08:53:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Bayesian Subspace Hidden Markov Modelによる音声単位発見（Bayesian Subspace Hidden Markov Model for Acoustic Unit Discovery）</news:title>
   <news:publication_date>2026-08-28T08:53:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728143</loc>
  <lastmod>2026-08-28T08:53:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画における時空間的識別表現の位置づけ（Referring to Objects in Videos using Spatio-Temporal Identifying Descriptions）</news:title>
   <news:publication_date>2026-08-28T08:53:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728141</loc>
  <lastmod>2026-08-28T08:53:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>新規Wikipedia利用者の関心を引き出す自動生成アンケート（Eliciting New Wikipedia Users’ Interests via Automatically Mined Questionnaires: For a Warm Welcome, Not a Cold Start）</news:title>
   <news:publication_date>2026-08-28T08:53:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728139</loc>
  <lastmod>2026-08-28T08:52:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関数分解によるモデル複雑度の定量化と解釈性向上（Quantifying Model Complexity via Functional Decomposition for Better Post-Hoc Interpretability）</news:title>
   <news:publication_date>2026-08-28T08:52:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728137</loc>
  <lastmod>2026-08-28T08:52:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率化された密集型ビデオキャプショニング（Streamlined Dense Video Captioning）</news:title>
   <news:publication_date>2026-08-28T08:52:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728135</loc>
  <lastmod>2026-08-28T08:52:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lidarとステレオ画像のノイズに強い融合法（Noise-Aware Unsupervised Deep Lidar–Stereo Fusion）</news:title>
   <news:publication_date>2026-08-28T08:52:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728133</loc>
  <lastmod>2026-08-28T08:52:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粘弾性梁の減衰制御—振動特性を設計する視点（Damping control in viscoelastic beam dynamics）</news:title>
   <news:publication_date>2026-08-28T08:52:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728131</loc>
  <lastmod>2026-08-28T08:00:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>キクチ階層とテンソルPCA（The Kikuchi Hierarchy and Tensor PCA）</news:title>
   <news:publication_date>2026-08-28T08:00:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728129</loc>
  <lastmod>2026-08-28T08:00:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深いランダムネットワークの学習可能性（On the Learnability of Deep Random Networks）</news:title>
   <news:publication_date>2026-08-28T08:00:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728127</loc>
  <lastmod>2026-08-28T07:59:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極端な画像符号化のためのマルチスケール自己符号化器と生成的敵対的最適化（Extreme Image Coding via Multiscale Autoencoders with Generative Adversarial Optimization）</news:title>
   <news:publication_date>2026-08-28T07:59:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728125</loc>
  <lastmod>2026-08-28T07:59:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DPNNを用いた衝撃問題の画像ベース再構成（Image-based reconstruction for the impact problems by using DPNNs）</news:title>
   <news:publication_date>2026-08-28T07:59:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728123</loc>
  <lastmod>2026-08-28T07:59:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>静止・動的シーンのための教師なし深層エピポーラフロー（Unsupervised Deep Epipolar Flow for Stationary or Dynamic Scenes）</news:title>
   <news:publication_date>2026-08-28T07:59:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728121</loc>
  <lastmod>2026-08-28T07:58:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱監督の人物再識別：微分可能グラフィカル学習と大規模ベンチマークの提示（Weakly Supervised Person Re-ID: Differentiable Graphical Learning and A New Benchmark）</news:title>
   <news:publication_date>2026-08-28T07:58:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728119</loc>
  <lastmod>2026-08-28T07:58:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分解ベースの転移距離計量学習による画像分類の改善（Decomposition based Transfer Distance Metric Learning for Image Classification）</news:title>
   <news:publication_date>2026-08-28T07:58:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728117</loc>
  <lastmod>2026-08-28T07:06:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語と音楽における長期依存性の統計的検証（A Statistical Investigation of Long Memory in Language and Music）</news:title>
   <news:publication_date>2026-08-28T07:06:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728115</loc>
  <lastmod>2026-08-28T07:06:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生の音声から感情を直接学ぶ技術（Direct Modelling of Speech Emotion from Raw Speech）</news:title>
   <news:publication_date>2026-08-28T07:06:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728113</loc>
  <lastmod>2026-08-28T07:06:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>向心SGDによる複雑構造を持つ極深畳み込みネットワークの剪定（Centripetal SGD for Pruning Very Deep Convolutional Networks with Complicated Structure）</news:title>
   <news:publication_date>2026-08-28T07:06:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728111</loc>
  <lastmod>2026-08-28T07:05:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小規模データでの会話テキストによる抑うつ検出（Text-based depression detection on sparse data）</news:title>
   <news:publication_date>2026-08-28T07:05:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728109</loc>
  <lastmod>2026-08-28T07:05:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱教師あり人物再識別の実務的意義（Weakly Supervised Person Re-Identification）</news:title>
   <news:publication_date>2026-08-28T07:05:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728107</loc>
  <lastmod>2026-08-28T07:04:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平行マニピュレータの運動学合成とニューラルネットワーク（Kinematic Synthesis of Parallel Manipulator via Neural Network Approach）</news:title>
   <news:publication_date>2026-08-28T07:04:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728105</loc>
  <lastmod>2026-08-28T07:04:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深く覆い隠された活動銀河核（AGN）の実像を明らかにする—Chandra Deep Fieldsにおける高吸収・コンプトン厚AGNのX線分光と長期変動分析（Piercing Through Highly Obscured and Compton-thick AGNs in the Chandra Deep Fields: I. X-ray Spectral and Long-term Variability Analyses）</news:title>
   <news:publication_date>2026-08-28T07:04:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728103</loc>
  <lastmod>2026-08-28T06:13:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>柔らかいロボットの「触覚」の可視化—内蔵カメラで3D形状をリアルタイム推定する手法（Real-time Soft Body 3D Proprioception via Deep Vision-based Sensing）</news:title>
   <news:publication_date>2026-08-28T06:13:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728101</loc>
  <lastmod>2026-08-28T06:12:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WeNet：再帰型ネットワークのアーキテクチャ探索のための重み付きネットワーク（WeNet: Weighted Networks for Recurrent Network Architecture Search）</news:title>
   <news:publication_date>2026-08-28T06:12:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728099</loc>
  <lastmod>2026-08-28T06:12:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル向け自動ポートレートマッティングの実時間化（Towards Real-Time Automatic Portrait Matting on Mobile Devices）</news:title>
   <news:publication_date>2026-08-28T06:12:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728097</loc>
  <lastmod>2026-08-28T06:12:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル向けリアルタイムキーワード検出における時間方向畳み込みの威力（Temporal Convolution for Real-time Keyword Spotting on Mobile Devices）</news:title>
   <news:publication_date>2026-08-28T06:12:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728095</loc>
  <lastmod>2026-08-28T06:12:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワンビット送受信機を用いたマルチホップMU-MIMOの教師あり学習による検出（Supervised-Learning for Multi-Hop MU-MIMO Communications with One-Bit Transceivers）</news:title>
   <news:publication_date>2026-08-28T06:12:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728093</loc>
  <lastmod>2026-08-28T06:11:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>希少語表現を強化する埋め込み行列拡張（Enriching Rare Word Representations in Neural Language Models by Embedding Matrix Augmentation）</news:title>
   <news:publication_date>2026-08-28T06:11:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728091</loc>
  <lastmod>2026-08-28T06:11:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸正則化を用いた二値行列補完（Binary Matrix Completion with Nonconvex Regularizers）</news:title>
   <news:publication_date>2026-08-28T06:11:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728089</loc>
  <lastmod>2026-08-28T05:20:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アンカーを捨てた物体検出の刷新（FoveaBox: Beyond Anchor-Based Object Detection）</news:title>
   <news:publication_date>2026-08-28T05:20:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728087</loc>
  <lastmod>2026-08-28T05:20:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小包含球の再考：安定性と亜線形時間アルゴリズム（Minimum Enclosing Ball Revisited: Stability and Sub-linear Time Algorithms）</news:title>
   <news:publication_date>2026-08-28T05:20:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728085</loc>
  <lastmod>2026-08-28T05:20:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ非パラメトリックによる多音源モデリングを用いた決定論的ブラインド音源分離（BAYESIAN NON-PARAMETRIC MULTI-SOURCE MODELLING BASED DETERMINED BLIND SOURCE SEPARATION）</news:title>
   <news:publication_date>2026-08-28T05:20:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728083</loc>
  <lastmod>2026-08-28T05:19:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタを学習しながら行う1ビット行列補完（Cluster Developing 1-Bit Matrix Completion）</news:title>
   <news:publication_date>2026-08-28T05:19:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728081</loc>
  <lastmod>2026-08-28T05:18:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>資源制約下のニューラルアーキテクチャ探索と部分集合性の可能性（Resource Constrained Neural Network Architecture Search: Will a Submodularity Assumption Help?）</news:title>
   <news:publication_date>2026-08-28T05:18:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728079</loc>
  <lastmod>2026-08-28T05:18:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル向け軽量畳み込みネットワークの新設計（ANTNets: Mobile Convolutional Neural Networks for Resource Efﬁcient Image Classiﬁcation）</news:title>
   <news:publication_date>2026-08-28T05:18:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728077</loc>
  <lastmod>2026-08-28T05:18:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>金属ガラスにおける空隙分布と塑性不均一性を結ぶ学習可能な枠組み（A transferable machine-learning framework linking interstice distribution and plastic heterogeneity in metallic glasses）</news:title>
   <news:publication_date>2026-08-28T05:18:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728075</loc>
  <lastmod>2026-08-28T04:26:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルウェアに対する回避攻撃と防御（Malware Evasion Attack and Defense）</news:title>
   <news:publication_date>2026-08-28T04:26:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728073</loc>
  <lastmod>2026-08-28T04:26:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ココナッツと島民が教えるボルツマン分布の直感（Coconuts and Islanders: A Statistics-First Guide to the Boltzmann Distribution）</news:title>
   <news:publication_date>2026-08-28T04:26:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728071</loc>
  <lastmod>2026-08-28T04:25:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間領域における音声・映像同時分離（TIME DOMAIN AUDIO VISUAL SPEECH SEPARATION）</news:title>
   <news:publication_date>2026-08-28T04:25:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728069</loc>
  <lastmod>2026-08-28T04:25:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>微分可能な凸最適化を用いたメタラーニング（Meta-Learning with Differentiable Convex Optimization）</news:title>
   <news:publication_date>2026-08-28T04:25:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728067</loc>
  <lastmod>2026-08-28T04:24:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表面欠陥のリアルタイム分類に向けたCNN設計（Surface Defect Classification in Real-Time Using Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-28T04:24:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728065</loc>
  <lastmod>2026-08-28T04:24:52Z</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RNN文法の学習法（Unsupervised Recurrent Neural Network Grammars）</news:title>
   <news:publication_date>2026-08-28T04:24:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728063</loc>
  <lastmod>2026-08-28T04:24:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層GCNの訓練手法が拓く可能性（DeepGCNs: Can GCNs Go as Deep as CNNs?）</news:title>
   <news:publication_date>2026-08-28T04:24:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728061</loc>
  <lastmod>2026-08-28T03:33:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話構造を自動で見つける技術（Unsupervised Dialog Structure Learning）</news:title>
   <news:publication_date>2026-08-28T03:33:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728059</loc>
  <lastmod>2026-08-28T03:33:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報ボトルネックと深層学習への応用（Information Bottleneck and its Applications in Deep Learning）</news:title>
   <news:publication_date>2026-08-28T03:33:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728057</loc>
  <lastmod>2026-08-28T03:32:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元データ下での二重頑健ℓ1正則化による因果推定の統一的手法（A unifying approach for doubly-robust ℓ1 regularized estimation of causal contrasts）</news:title>
   <news:publication_date>2026-08-28T03:32:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728055</loc>
  <lastmod>2026-08-28T03:32:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子分子動力学のためのベイズ機械学習（Bayesian machine learning for quantum molecular dynamics）</news:title>
   <news:publication_date>2026-08-28T03:32:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728053</loc>
  <lastmod>2026-08-28T03:32:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェアラブルからの連続睡眠モニタリングに適応する教師なし転移学習（An unsupervised transfer learning algorithm for sleep monitoring）</news:title>
   <news:publication_date>2026-08-28T03:32:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728051</loc>
  <lastmod>2026-08-28T03:31:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の視覚計測を用いて手書き文書の転写精度を改善する（Measuring Human Perception to Improve Handwritten Document Transcription）</news:title>
   <news:publication_date>2026-08-28T03:31:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728049</loc>
  <lastmod>2026-08-28T03:31:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合画像改竄の深層局所化（Deep Localization of Mixed Image Tampering Techniques）</news:title>
   <news:publication_date>2026-08-28T03:31:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728047</loc>
  <lastmod>2026-08-28T02:40:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトルX線投影画像における教師なし材料セグメンテーションの実証（Unsupervised Learning Methods in X-ray Spectral Imaging Material Segmentation）</news:title>
   <news:publication_date>2026-08-28T02:40:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728045</loc>
  <lastmod>2026-08-28T02:40:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>患者別シリコーン製僧帽弁モデルによる外科トレーニングの革新（Flexible and Comprehensive Patient-Specific Mitral Valve Silicone Models with Chordae Tendinae Made From 3D-Printable Molds）</news:title>
   <news:publication_date>2026-08-28T02:40:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728043</loc>
  <lastmod>2026-08-28T02:40:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neoに学ぶ学習型クエリ最適化（Neo: A Learned Query Optimizer）</news:title>
   <news:publication_date>2026-08-28T02:40:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728041</loc>
  <lastmod>2026-08-28T02:39:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地質学における生成対抗ネットワークを用いた確率的入力のパラメータ化 (Parametrization of stochastic inputs using generative adversarial networks with application in geology)</news:title>
   <news:publication_date>2026-08-28T02:39:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728039</loc>
  <lastmod>2026-08-28T02:39:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アペックス・タイムネットワークによるクロスデータセット微表情認識（A Novel Apex-Time Network for Cross-Dataset Micro-Expression Recognition）</news:title>
   <news:publication_date>2026-08-28T02:39:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728037</loc>
  <lastmod>2026-08-28T02:38:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸機械学習における局所最小値は全局最小値である（Every Local Minimum Value Is the Global Minimum Value of Induced Model in Nonconvex Machine Learning）</news:title>
   <news:publication_date>2026-08-28T02:38:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728035</loc>
  <lastmod>2026-08-28T02:38:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所化された関連ベクトル機械によるパターン分類（Proposing a Localized Relevance Vector Machine for Pattern Classification）</news:title>
   <news:publication_date>2026-08-28T02:38:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728033</loc>
  <lastmod>2026-08-28T01:46:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高加速度の弾道運動を筋肉駆動ロボットで学習制御する（Learning to Control Highly Accelerated Ballistic Movements on Muscular Robots）</news:title>
   <news:publication_date>2026-08-28T01:46:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728031</loc>
  <lastmod>2026-08-28T01:46:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声モデル事前学習によるエンドツーエンド音声理解の改善（Speech Model Pre-training for End-to-End Spoken Language Understanding）</news:title>
   <news:publication_date>2026-08-28T01:46:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728029</loc>
  <lastmod>2026-08-28T01:46:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模アンテナアレイのためのビームフォーミング設計を深層学習で（Beamforming Design for Large-Scale Antenna Arrays Using Deep Learning）</news:title>
   <news:publication_date>2026-08-28T01:46:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728027</loc>
  <lastmod>2026-08-28T01:46:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ推定による混合多項ロジットモデルの実務的意義（Bayesian Estimation of Mixed Multinomial Logit Models: Advances and Simulation-Based Evaluations）</news:title>
   <news:publication_date>2026-08-28T01:46:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728025</loc>
  <lastmod>2026-08-28T01:45:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>抵抗性RAMベースの2値ニューラルネットワークの卓越したビット誤り耐性（Outstanding Bit Error Tolerance of Resistive RAM-Based Binarized Neural Networks）</news:title>
   <news:publication_date>2026-08-28T01:45:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728023</loc>
  <lastmod>2026-08-28T01:45:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索木を使わないオンライン計画とExpert Iterationの革新（Policy Gradient Search: Online Planning and Expert Iteration without Search Trees）</news:title>
   <news:publication_date>2026-08-28T01:45:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728021</loc>
  <lastmod>2026-08-28T01:45:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>系列→要約→復元の自己符号化で学ぶ教師なし文圧縮（Differentiable Sequence-to-Sequence-to-Sequence Autoencoder for Unsupervised Abstractive Sentence Compression）</news:title>
   <news:publication_date>2026-08-28T01:45:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728019</loc>
  <lastmod>2026-08-28T00:53:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小児MRIのリアルタイム画質評価（Real-Time Quality Assessment of Pediatric MRI via Semi-Supervised Deep Nonlocal Residual Neural Networks）</news:title>
   <news:publication_date>2026-08-28T00:53:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728017</loc>
  <lastmod>2026-08-28T00:52:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群衆の歩行者検出を改善する適応的NMS（Adaptive NMS: Reﬁning Pedestrian Detection in a Crowd）</news:title>
   <news:publication_date>2026-08-28T00:52:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728015</loc>
  <lastmod>2026-08-28T00:52:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重要人物検出のための関係学習（Learning to Learn Relation for Important People Detection in Still Images）</news:title>
   <news:publication_date>2026-08-28T00:52:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728013</loc>
  <lastmod>2026-08-28T00:51:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベクトル形式スケッチを学習するGANの手法（Teaching GANS to Sketch in Vector Format）</news:title>
   <news:publication_date>2026-08-28T00:51:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728011</loc>
  <lastmod>2026-08-28T00:51:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師から学ぶ距離学習：小型ネットワークで高品質な画像埋め込みを得る方法（Learning Metrics from Teachers: Compact Networks for Image Embedding）</news:title>
   <news:publication_date>2026-08-28T00:51:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728009</loc>
  <lastmod>2026-08-28T00:51:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VAEを用いた深層話者埋め込みの正則化（VAE-based regularization for deep speaker embedding）</news:title>
   <news:publication_date>2026-08-28T00:51:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728007</loc>
  <lastmod>2026-08-28T00:51:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カリキュラム学習が深層ネットワークの訓練にもたらす力（On The Power of Curriculum Learning in Training Deep Networks）</news:title>
   <news:publication_date>2026-08-28T00:51:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728005</loc>
  <lastmod>2026-08-27T23:59:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頭蓋内脳波と自動特徴学習によるてんかん発作予測（Human Intracranial EEG Quantitative Analysis and Automatic Feature Learning for Epileptic Seizure Prediction）</news:title>
   <news:publication_date>2026-08-27T23:59:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728003</loc>
  <lastmod>2026-08-27T23:49:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチコア多モード光ファイバと深層学習による高速スペクトル復元（Deep learning enabled real time speckle recognition and hyperspectral imaging using a multimode fibre array）</news:title>
   <news:publication_date>2026-08-27T23:49:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728001</loc>
  <lastmod>2026-08-27T23:48:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自閉スペクトラム症の顔情動解析システム（A Facial Affect Analysis System for Autism Spectrum Disorder）</news:title>
   <news:publication_date>2026-08-27T23:48:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727999</loc>
  <lastmod>2026-08-27T23:47:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画の自己教師付き時空間表現学習（Self-supervised Spatio-temporal Representation Learning for Videos）</news:title>
   <news:publication_date>2026-08-27T23:47:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727997</loc>
  <lastmod>2026-08-27T23:47:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前学習ユニットとランダムユニットの共同学習によるドメイン適応（Joint Learning of Pre-Trained and Random Units for Domain Adaptation in Part-of-Speech Tagging）</news:title>
   <news:publication_date>2026-08-27T23:47:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727995</loc>
  <lastmod>2026-08-27T23:47:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Redditにおけるマクロ規範違反検出のハイブリッド手法（Hybrid Approaches to Detect Comments Violating Macro Norms on Reddit）</news:title>
   <news:publication_date>2026-08-27T23:47:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727993</loc>
  <lastmod>2026-08-27T23:47:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>競争比とレグレットの両立を目指すオンラインアルゴリズムの方法論（Competitive ratio versus regret minimization: achieving the best of both worlds）</news:title>
   <news:publication_date>2026-08-27T23:47:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727991</loc>
  <lastmod>2026-08-27T22:54:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AMSGRADの収束証明の再検討と改良版（On the Convergence Proof of AMSGrad and a New Version）</news:title>
   <news:publication_date>2026-08-27T22:54:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727989</loc>
  <lastmod>2026-08-27T22:54:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内部脅威検知の再設計 — esINSIDERの要点と経営判断への示唆 (Reframing Threat Detection: Inside esINSIDER)</news:title>
   <news:publication_date>2026-08-27T22:54:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727987</loc>
  <lastmod>2026-08-27T22:54:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチラベル画像認識を変えるグラフ畳み込みネットワーク（Multi-Label Image Recognition with Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-08-27T22:54:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727985</loc>
  <lastmod>2026-08-27T22:53:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>より微妙な比較を可能にする（COMPARE MORE NUANCED: PAIRWISE ALIGNMENT BILINEAR NETWORK FOR FEW-SHOT FINE-GRAINED LEARNING）</news:title>
   <news:publication_date>2026-08-27T22:53:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727983</loc>
  <lastmod>2026-08-27T22:53:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ダイレーテッド・インセプションネットワークによる視覚的注目予測（A Dilated Inception Network for Visual Saliency Prediction）</news:title>
   <news:publication_date>2026-08-27T22:53:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727981</loc>
  <lastmod>2026-08-27T22:52:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汎用移動マニピュレータによる能動的食事支援の設計と評価（Active Robot-Assisted Feeding with a General-Purpose Mobile Manipulator: Design, Evaluation, and Lessons Learned）</news:title>
   <news:publication_date>2026-08-27T22:52:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727979</loc>
  <lastmod>2026-08-27T22:52:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的に接続するニューラルネットワークの意義（Adaptively Connected Neural Networks）</news:title>
   <news:publication_date>2026-08-27T22:52:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727977</loc>
  <lastmod>2026-08-27T22:01:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークによる画像・映像圧縮の概観（Image and Video Compression with Neural Networks: A Review）</news:title>
   <news:publication_date>2026-08-27T22:01:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727975</loc>
  <lastmod>2026-08-27T22:01:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所差分プライバシーにおける相互作用の役割（The Role of Interactivity in Local Differential Privacy）</news:title>
   <news:publication_date>2026-08-27T22:01:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727973</loc>
  <lastmod>2026-08-27T22:01:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速教師あり離散ハッシング（Fast Supervised Discrete Hashing）</news:title>
   <news:publication_date>2026-08-27T22:01:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727971</loc>
  <lastmod>2026-08-27T22:00:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズと欠損を含むデータの精度行列推定（Precision Matrix Estimation with Noisy and Missing Data）</news:title>
   <news:publication_date>2026-08-27T22:00:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727969</loc>
  <lastmod>2026-08-27T22:00:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Supervised Discrete Hashing with Relaxation（Supervised Discrete Hashing with Relaxation）</news:title>
   <news:publication_date>2026-08-27T22:00:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727967</loc>
  <lastmod>2026-08-27T21:59:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期的車両位置特定のための再帰的知識蒸留（Long-Term Vehicle Localization by Recursive Knowledge Distillation）</news:title>
   <news:publication_date>2026-08-27T21:59:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727965</loc>
  <lastmod>2026-08-27T21:59:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模環境での変化検出を一段速くする深層3Dニューラルコードによる検索手法（Scalable Change Retrieval Using Deep 3D Neural Codes）</news:title>
   <news:publication_date>2026-08-27T21:59:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727963</loc>
  <lastmod>2026-08-27T21:08:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PDFマルウェア分類器の堅牢な訓練（On Training Robust PDF Malware Classifiers）</news:title>
   <news:publication_date>2026-08-27T21:08:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727961</loc>
  <lastmod>2026-08-27T21:08:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間注意プーリングによる音響シーン分類の新展開（Spatio-Temporal Attention Pooling for Audio Scene Classification）</news:title>
   <news:publication_date>2026-08-27T21:08:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727959</loc>
  <lastmod>2026-08-27T21:08:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>慣性型ブレグマン近接勾配法における凸–凹バックトラッキング（Convex-Concave Backtracking for Inertial Bregman Proximal Gradient Algorithms in Non-Convex Optimization）</news:title>
   <news:publication_date>2026-08-27T21:08:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727957</loc>
  <lastmod>2026-08-27T21:07:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データで予測するオピオイド使用障害リスク（A Big Data Analytics Framework to Predict the Risk of Opioid Use Disorder）</news:title>
   <news:publication_date>2026-08-27T21:07:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727955</loc>
  <lastmod>2026-08-27T21:07:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化ベイジアン最小二乗方策反復（Randomised Bayesian Least-Squares Policy Iteration）</news:title>
   <news:publication_date>2026-08-27T21:07:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727953</loc>
  <lastmod>2026-08-27T21:07:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2500FPS超の高密度3D顔復元：テクスチャと形状の同時メッシュ畳み込みデコーダ（Dense 3D Face Decoding over 2500FPS: Joint Texture &amp;amp; Shape Convolutional Mesh Decoders）</news:title>
   <news:publication_date>2026-08-27T21:07:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727951</loc>
  <lastmod>2026-08-27T21:06:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベル付き混合特徴データの可視化（Visualization of Labeled Mixed-featured Datasets）</news:title>
   <news:publication_date>2026-08-27T21:06:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727949</loc>
  <lastmod>2026-08-27T20:15:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一スピーカーTacotronを応用した少量データ音声変換の実用化可能性（Taco-VC: A Single Speaker Tacotron based Voice Conversion with Limited Data）</news:title>
   <news:publication_date>2026-08-27T20:15:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727947</loc>
  <lastmod>2026-08-27T20:14:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンス単位のメタ正規化がもたらす現場的価値（Instance-Level Meta Normalization）</news:title>
   <news:publication_date>2026-08-27T20:14:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727945</loc>
  <lastmod>2026-08-27T20:13:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Split Batch Normalizationによる半教師あり学習の改善（Split Batch Normalization: Improving Semi-Supervised Learning under Domain Shift）</news:title>
   <news:publication_date>2026-08-27T20:13:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727943</loc>
  <lastmod>2026-08-27T20:13:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LP-3DCNNの局所位相検出とReLPVブロック（LP-3DCNN: Unveiling Local Phase in 3D Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-27T20:13:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727941</loc>
  <lastmod>2026-08-27T20:13:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepSEED：肺結節検出のための3D Squeeze-and-Excitation エンコーダ・デコーダ CNN (DeepSEED: 3D Squeeze-and-Excitation Encoder-Decoder Convolutional Neural Networks for Pulmonary Nodule Detection)</news:title>
   <news:publication_date>2026-08-27T20:13:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727939</loc>
  <lastmod>2026-08-27T20:13:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コスト認識型チャンネル選択による逐次ネットワーク剪定（C2S2: Cost-aware Channel Sparse Selection for Progressive Network Pruning）</news:title>
   <news:publication_date>2026-08-27T20:13:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727937</loc>
  <lastmod>2026-08-27T20:12:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーパーティザンニュース検出とプロパガンダ特徴の応用（Team QCRI-MIT at SemEval-2019 Task 4: Propaganda Analysis Meets Hyperpartisan News Detection）</news:title>
   <news:publication_date>2026-08-27T20:12:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727935</loc>
  <lastmod>2026-08-27T19:21:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AWGN学習型デノイザーと実世界ノイズの出会い（When AWGN-based Denoiser Meets Real Noises）</news:title>
   <news:publication_date>2026-08-27T19:21:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727933</loc>
  <lastmod>2026-08-27T19:21:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VATEX: 多言語・大規模動画データセットがもたらす実務インパクト（VATEX: A Large-Scale, High-Quality Multilingual Dataset for Video-and-Language Research）</news:title>
   <news:publication_date>2026-08-27T19:21:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727931</loc>
  <lastmod>2026-08-27T19:21:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークおよびホストベースの侵入検知システムに関する総説（A Compendium on Network and Host based Intrusion Detection Systems）</news:title>
   <news:publication_date>2026-08-27T19:21:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727929</loc>
  <lastmod>2026-08-27T19:20:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスタスク学習による音響タギング・音イベント検出・空間局在化の共通基盤（CROSS-TASK LEARNING FOR AUDIO TAGGING, SOUND EVENT DETECTION AND SPATIAL LOCALIZATION: DCASE 2019 BASELINE SYSTEMS）</news:title>
   <news:publication_date>2026-08-27T19:20:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727927</loc>
  <lastmod>2026-08-27T19:20:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サリエンシーで補完する少数ショット学習（Few-shot Learning via Saliency-guided Hallucination of Samples）</news:title>
   <news:publication_date>2026-08-27T19:20:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727925</loc>
  <lastmod>2026-08-27T19:20:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォトリアリスティック環境における点群認識を用いたエンボディド質問応答（Embodied Question Answering in Photorealistic Environments with Point Cloud Perception）</news:title>
   <news:publication_date>2026-08-27T19:20:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727923</loc>
  <lastmod>2026-08-27T19:19:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層スタック型階層多重パッチネットワークによる画像ブレ補正（Deep Stacked Hierarchical Multi-patch Network for Image Deblurring）</news:title>
   <news:publication_date>2026-08-27T19:19:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727921</loc>
  <lastmod>2026-08-27T18:28:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検索と抽出を組み合わせたキーフレーズ生成の統合アプローチ（An Integrated Approach for Keyphrase Generation via Exploring the Power of Retrieval and Extraction）</news:title>
   <news:publication_date>2026-08-27T18:28:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727919</loc>
  <lastmod>2026-08-27T18:27:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元確率的最適化における低ランク正則化（Regularized Sample Average Approximation for High-Dimensional Stochastic Optimization Under Low-Rankness）</news:title>
   <news:publication_date>2026-08-27T18:27:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727917</loc>
  <lastmod>2026-08-27T18:27:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トークンレベルのアンサンブル蒸留によるG2P変換の改善（Token-Level Ensemble Distillation for Grapheme-to-Phoneme Conversion）</news:title>
   <news:publication_date>2026-08-27T18:27:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727915</loc>
  <lastmod>2026-08-27T18:26:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種行動空間における強化付き模倣（Reinforced Imitation in Heterogeneous Action Space）</news:title>
   <news:publication_date>2026-08-27T18:26:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727913</loc>
  <lastmod>2026-08-27T18:26:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Iterative Normalizationによる効率的なホワイトニングの実現（Iterative Normalization: Beyond Standardization towards Efficient Whitening）</news:title>
   <news:publication_date>2026-08-27T18:26:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727911</loc>
  <lastmod>2026-08-27T18:26:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バスの所要時間予測（Bus Travel Time Prediction: A log-normal Auto-Regressive (AR) Modeling Approach）</news:title>
   <news:publication_date>2026-08-27T18:26:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727909</loc>
  <lastmod>2026-08-27T18:25:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成モデルの潜在空間における特徴ベース補間と測地線（Feature-Based Interpolation and Geodesics in the Latent Spaces of Generative Models）</news:title>
   <news:publication_date>2026-08-27T18:25:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727907</loc>
  <lastmod>2026-08-27T17:34:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カメラを意識した教師なしドメイン適応による人物再識別（A Novel Unsupervised Camera-aware Domain Adaptation Framework for Person Re-identiﬁcation）</news:title>
   <news:publication_date>2026-08-27T17:34:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727905</loc>
  <lastmod>2026-08-27T17:34:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リングメッシュ：多数コアアクセラレータ向けのスケーラブルで高性能な接続方式 (Ring-Mesh: A Scalable and High-Performance Approach for Manycore Accelerators)</news:title>
   <news:publication_date>2026-08-27T17:34:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727903</loc>
  <lastmod>2026-08-27T17:33:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ拡張不変性と広がりを利用した教師なし埋め込み学習（Unsupervised Embedding Learning via Invariant and Spreading Instance Feature）</news:title>
   <news:publication_date>2026-08-27T17:33:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727901</loc>
  <lastmod>2026-08-27T17:32:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的ネットワーク埋め込みの増分学習フレームワーク（FILDNE: A Framework for Incremental Learning of Dynamic Networks Embeddings）</news:title>
   <news:publication_date>2026-08-27T17:32:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727899</loc>
  <lastmod>2026-08-27T17:32:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化された音声強調を目指すGAN（Towards Generalized Speech Enhancement with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-08-27T17:32:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727897</loc>
  <lastmod>2026-08-27T17:32:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数の自己教師ありタスクから学ぶ問題非依存な音声表現（Learning Problem-agnostic Speech Representations from Multiple Self-supervised Tasks）</news:title>
   <news:publication_date>2026-08-27T17:32:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727895</loc>
  <lastmod>2026-08-27T17:32:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈認識型の人間運動予測（Context-aware Human Motion Prediction）</news:title>
   <news:publication_date>2026-08-27T17:32:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727893</loc>
  <lastmod>2026-08-27T16:40:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的RGB-D融合による深層表面法線推定（Deep Surface Normal Estimation with Hierarchical RGB-D Fusion）</news:title>
   <news:publication_date>2026-08-27T16:40:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727891</loc>
  <lastmod>2026-08-27T16:40:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バックトラックレス整列空間グラフ畳み込みネットワークの図解（Learning Backtrackless Aligned-Spatial Graph Convolutional Networks for Graph Classification）</news:title>
   <news:publication_date>2026-08-27T16:40:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727889</loc>
  <lastmod>2026-08-27T16:40:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層畳み込みニューラルネットワークのための効率的かつ有効なドロップアウト（Efficient and Effective Dropout for Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-27T16:40:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727887</loc>
  <lastmod>2026-08-27T16:39:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼深度推定のCNN可視化（Visualization of Convolutional Neural Networks for Monocular Depth Estimation）</news:title>
   <news:publication_date>2026-08-27T16:39:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727885</loc>
  <lastmod>2026-08-27T16:39:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再識別を用いたテクスチャ生成（Re-Identification Supervised Texture Generation）</news:title>
   <news:publication_date>2026-08-27T16:39:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727883</loc>
  <lastmod>2026-08-27T16:39:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゾーニング特徴を用いたパシュトー手書き文字の認識（KNN and ANN-based Recognition of Handwritten Pashto Letters using Zoning Features）</news:title>
   <news:publication_date>2026-08-27T16:39:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727881</loc>
  <lastmod>2026-08-27T16:38:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在次元とコミュニティ数のベイジアン推定（Bayesian estimation of the latent dimension and communities in stochastic blockmodels）</news:title>
   <news:publication_date>2026-08-27T16:38:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727879</loc>
  <lastmod>2026-08-27T15:47:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復カーネル補正によるブラインド超解像（Blind Super-Resolution With Iterative Kernel Correction）</news:title>
   <news:publication_date>2026-08-27T15:47:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727877</loc>
  <lastmod>2026-08-27T15:47:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カメラレンズ超解像（Camera Lens Super-Resolution）</news:title>
   <news:publication_date>2026-08-27T15:47:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727875</loc>
  <lastmod>2026-08-27T15:47:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味解析を用いた教師なし人物画像生成（Unsupervised Person Image Generation with Semantic Parsing Transformation）</news:title>
   <news:publication_date>2026-08-27T15:47:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727873</loc>
  <lastmod>2026-08-27T15:46:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所一貫性を目指した物体計数の制約付き多段畳み込みニューラルネットワーク（Towards Locally Consistent Object Counting with Constrained Multi-stage Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-27T15:46:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727871</loc>
  <lastmod>2026-08-27T15:46:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話システムの一貫性評価における含意手法（Evaluating Coherence in Dialogue Systems using Entailment）</news:title>
   <news:publication_date>2026-08-27T15:46:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727869</loc>
  <lastmod>2026-08-27T15:45:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己注意とガンベル部分集合サンプリングによる点群処理の革新（Modeling Point Clouds with Self-Attention and Gumbel Subset Sampling）</news:title>
   <news:publication_date>2026-08-27T15:45:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727867</loc>
  <lastmod>2026-08-27T15:45:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機能する注意機構を持つ強化学習（Reinforcement Learning with Attention that Works: A Self-Supervised Approach）</news:title>
   <news:publication_date>2026-08-27T15:45:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727865</loc>
  <lastmod>2026-08-27T14:53:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReMASC：現実的なリプレイ攻撃コーパスが示すVCS防御の本質（ReMASC: Realistic Replay Attack Corpus for Voice Controlled Systems）</news:title>
   <news:publication_date>2026-08-27T14:53:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727863</loc>
  <lastmod>2026-08-27T14:53:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公共圏における知覚を写し取る単純な動的単語埋め込み（Simple dynamic word embeddings for mapping perceptions in the public sphere）</news:title>
   <news:publication_date>2026-08-27T14:53:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727861</loc>
  <lastmod>2026-08-27T14:52:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BridgeNetによる連続性配慮型確率ネットワークで年齢推定を精度向上（BridgeNet: A Continuity-Aware Probabilistic Network for Age Estimation）</news:title>
   <news:publication_date>2026-08-27T14:52:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727859</loc>
  <lastmod>2026-08-27T14:52:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズのある点群の局所正則化による幾何推定とデータ解析の改善（LOCAL REGULARIZATION OF NOISY POINT CLOUDS: IMPROVED GLOBAL GEOMETRIC ESTIMATES AND DATA ANALYSIS）</news:title>
   <news:publication_date>2026-08-27T14:52:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727857</loc>
  <lastmod>2026-08-27T14:52:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BERTは領域が変わると不安定になる（ThisIsCompetition at SemEval-2019 Task 9: BERT is unstable for out-of-domain samples）</news:title>
   <news:publication_date>2026-08-27T14:52:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727855</loc>
  <lastmod>2026-08-27T14:52:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Semantic Graph Convolutional Networksによる3D人間姿勢推定の革新（Semantic Graph Convolutional Networks for 3D Human Pose Regression）</news:title>
   <news:publication_date>2026-08-27T14:52:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727853</loc>
  <lastmod>2026-08-27T14:51:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的ネットワークモデルの普遍的検定に向けて（Toward Universal Testing of Dynamic Network Models）</news:title>
   <news:publication_date>2026-08-27T14:51:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727851</loc>
  <lastmod>2026-08-27T14:00:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>広域で検証された粗視化学習によるニューラルネットワーク気候パラメタリゼーション（Spatially Extended Tests of a Neural Network Parametrization Trained by Coarse-graining）</news:title>
   <news:publication_date>2026-08-27T14:00:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727849</loc>
  <lastmod>2026-08-27T14:00:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チーム学習における個人貢献の公正評価（Learning in teams: peer evaluation for fair assessment of individual contributions）</news:title>
   <news:publication_date>2026-08-27T14:00:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727847</loc>
  <lastmod>2026-08-27T13:59:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限られた写真から360度パノラマを再構築する技術（360 Panorama Synthesis from a Sparse Set of Images with Unknown Field of View）</news:title>
   <news:publication_date>2026-08-27T13:59:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727845</loc>
  <lastmod>2026-08-27T13:59:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈と断片特徴の効果的利用による固有表現認識（Effective Context and Fragment Feature Usage for Named Entity Recognition）</news:title>
   <news:publication_date>2026-08-27T13:59:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727843</loc>
  <lastmod>2026-08-27T13:58:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変長系列を固定長で扱う局所検出による固有表現認識のマルチタスク学習（A Multi-task Learning Approach for Named Entity Recognition using Local Detection）</news:title>
   <news:publication_date>2026-08-27T13:58:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727841</loc>
  <lastmod>2026-08-27T13:58:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNNのスケジューリング効率を測る指標と省メモリ化の可能性（Measuring scheduling efficiency of RNNs for NLP applications）</news:title>
   <news:publication_date>2026-08-27T13:58:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727839</loc>
  <lastmod>2026-08-27T13:57:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集団行動認識のための畳み込み関係推論機（Convolutional Relational Machine for Group Activity Recognition）</news:title>
   <news:publication_date>2026-08-27T13:57:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727837</loc>
  <lastmod>2026-08-27T13:06:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数の人間的嗜好を同時に学習に組み込む手法（Multi-Preference Actor Critic）</news:title>
   <news:publication_date>2026-08-27T13:06:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727835</loc>
  <lastmod>2026-08-27T13:06:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シングルキャリア指標変調によるIoT上り伝送（Single-Carrier Index Modulation for IoT Uplink）</news:title>
   <news:publication_date>2026-08-27T13:06:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727833</loc>
  <lastmod>2026-08-27T13:05:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限定された相互作用下での協調学習：分散探索に関する厳密な境界（Collaborative Learning with Limited Interaction: Tight Bounds for Distributed Exploration in Multi-Armed Bandits）</news:title>
   <news:publication_date>2026-08-27T13:05:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727831</loc>
  <lastmod>2026-08-27T13:05:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実世界における単眼3D人体姿勢推定の新展開（In the Wild Human Pose Estimation Using Explicit 2D Features and Intermediate 3D Representations）</news:title>
   <news:publication_date>2026-08-27T13:05:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727829</loc>
  <lastmod>2026-08-27T13:05:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>End-to-End畳み込み音響モデルJasper（Jasper: An End-to-End Convolutional Neural Acoustic Model）</news:title>
   <news:publication_date>2026-08-27T13:05:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727827</loc>
  <lastmod>2026-08-27T13:05:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習タスクの情報的複雑性と距離（The Information Complexity of Learning Tasks, their Structure and their Distance）</news:title>
   <news:publication_date>2026-08-27T13:05:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727825</loc>
  <lastmod>2026-08-27T13:04:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズ下の時系列を学習するRNNの振る舞い（Short note on the behavior of recurrent neural network for noisy dynamical system）</news:title>
   <news:publication_date>2026-08-27T13:04:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727823</loc>
  <lastmod>2026-08-27T12:13:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成・フィルタ・ランク：実運用対応NLGの文法性判定（Generate, Filter, and Rank: Grammaticality Classification for Production-Ready NLG Systems）</news:title>
   <news:publication_date>2026-08-27T12:13:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727821</loc>
  <lastmod>2026-08-27T12:13:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト検索から動画の瞬間を特定する弱監督学習（Weakly Supervised Video Moment Retrieval From Text Queries）</news:title>
   <news:publication_date>2026-08-27T12:13:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727819</loc>
  <lastmod>2026-08-27T12:12:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AMASSによるモーションキャプチャ統合の革新（AMASS: Archive of Motion Capture as Surface Shapes）</news:title>
   <news:publication_date>2026-08-27T12:12:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727817</loc>
  <lastmod>2026-08-27T12:12:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロバスト部分空間回復（Robust Subspace Recovery with Adversarial Outliers）</news:title>
   <news:publication_date>2026-08-27T12:12:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727815</loc>
  <lastmod>2026-08-27T12:12:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最密サブグラフ・最密サブマトリクスの凸最適化（Convex optimization for the densest subgraph and densest submatrix problems）</news:title>
   <news:publication_date>2026-08-27T12:12:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727813</loc>
  <lastmod>2026-08-27T12:12:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成方針によるタスク・環境横断の転移と適応（Synthesized Policies for Transfer and Adaptation across Tasks and Environments）</news:title>
   <news:publication_date>2026-08-27T12:12:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727811</loc>
  <lastmod>2026-08-27T12:11:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非同期行動列を生成する確率モデルの提案（A Variational Auto-Encoder Model for Stochastic Point Processes）</news:title>
   <news:publication_date>2026-08-27T12:11:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727809</loc>
  <lastmod>2026-08-27T11:20:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>荷電流深部散乱におけるチャーム生成の計測（Charm production in charged current deep inelastic scattering at HERA）</news:title>
   <news:publication_date>2026-08-27T11:20:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727807</loc>
  <lastmod>2026-08-27T11:20:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピクセルからプランへ：プランナーを模倣して学ぶ非把持操作（Pixels to Plans: Learning Non-Prehensile Manipulation by Imitating a Planner）</news:title>
   <news:publication_date>2026-08-27T11:20:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727805</loc>
  <lastmod>2026-08-27T11:19:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>「教師なし学習」という呼び方は誤解か？（Is ‘Unsupervised Learning’ a Misconceived Term?）</news:title>
   <news:publication_date>2026-08-27T11:19:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727803</loc>
  <lastmod>2026-08-27T11:19:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床ノートに対する注意機構の解析（An Analysis of Attention over Clinical Notes for Predictive Tasks）</news:title>
   <news:publication_date>2026-08-27T11:19:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727801</loc>
  <lastmod>2026-08-27T11:19:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Spatial CUSUMによる空間信号領域検出（Spatial CUSUM for Signal Region Detection）</news:title>
   <news:publication_date>2026-08-27T11:19:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727799</loc>
  <lastmod>2026-08-27T11:18:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生テキストから意味役割への言語横断的転送（Cross-Lingual Transfer of Semantic Roles: From Raw Text to Semantic Roles）</news:title>
   <news:publication_date>2026-08-27T11:18:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727797</loc>
  <lastmod>2026-08-27T11:18:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意の蒸留によるビデオ表現学習（Attention Distillation for Learning Video Representations）</news:title>
   <news:publication_date>2026-08-27T11:18:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727795</loc>
  <lastmod>2026-08-27T10:27:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低分解能スペクトルからの金属豊富型星（Am星）同定と機械学習の実務的意義（Metallic-Line Stars Identified from Low Resolution Spectra of LAMOST DR5）</news:title>
   <news:publication_date>2026-08-27T10:27:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727793</loc>
  <lastmod>2026-08-27T10:26:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声の未ラベルデータから汎用表現を作る手法（An Unsupervised Autoregressive Model for Speech Representation Learning）</news:title>
   <news:publication_date>2026-08-27T10:26:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727791</loc>
  <lastmod>2026-08-27T10:26:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HOList: 高階定理証明学習環境（HOList: An Environment for Machine Learning of Higher-Order Theorem Proving）</news:title>
   <news:publication_date>2026-08-27T10:26:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727789</loc>
  <lastmod>2026-08-27T10:26:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NELEC によるチャット文の感情検出の実務的示唆（NELEC at SemEval-2019 Task 3: Think Twice Before Going Deep）</news:title>
   <news:publication_date>2026-08-27T10:26:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727787</loc>
  <lastmod>2026-08-27T10:25:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ShapeMaskによる未学習カテゴリの物体分割の革新（ShapeMask: Learning to Segment Novel Objects by Reﬁning Shape Priors）</news:title>
   <news:publication_date>2026-08-27T10:25:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727785</loc>
  <lastmod>2026-08-27T10:25:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床文書における感情判定の領域適応の重要性（Distinguishing Clinical Sentiment: The Importance of Domain Adaptation in Psychiatric Patient Health Records）</news:title>
   <news:publication_date>2026-08-27T10:25:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727783</loc>
  <lastmod>2026-08-27T10:25:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組織の3レベルで読み解くアジリティ（Learning more from crossing levels: Investigating agility at three levels of the organization）</news:title>
   <news:publication_date>2026-08-27T10:25:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727781</loc>
  <lastmod>2026-08-27T09:33:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原始的内部運動に由来するハロースピン（Halo Spin from Primordial Inner Motions）</news:title>
   <news:publication_date>2026-08-27T09:33:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727779</loc>
  <lastmod>2026-08-27T09:33:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fishyscapes ベンチマーク：セマンティックセグメンテーションにおける盲点の測定（The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation）</news:title>
   <news:publication_date>2026-08-27T09:33:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727777</loc>
  <lastmod>2026-08-27T09:33:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セマンティック認識を組み込んだ知識保持でゼロショット・スケッチ検索を強化する（Semantic-Aware Knowledge Preservation for Zero-Shot Sketch-Based Image Retrieval）</news:title>
   <news:publication_date>2026-08-27T09:33:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727775</loc>
  <lastmod>2026-08-27T09:32:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理的構築に向けた構造化エージェント（Structured agents for physical construction）</news:title>
   <news:publication_date>2026-08-27T09:32:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727773</loc>
  <lastmod>2026-08-27T09:32:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様性を導入した隠れマルコフモデルによる系列ラベリング（Diversified Hidden Markov Models for Sequential Labeling）</news:title>
   <news:publication_date>2026-08-27T09:32:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727771</loc>
  <lastmod>2026-08-27T09:31:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学術論文タイトルを読みやすく変える手法（Improving Scientific Article Visibility by Neural Title Simplification）</news:title>
   <news:publication_date>2026-08-27T09:31:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727769</loc>
  <lastmod>2026-08-27T09:31:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化的手法で破局的忘却を減らす（Reducing catastrophic forgetting when evolving neural networks）</news:title>
   <news:publication_date>2026-08-27T09:31:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727767</loc>
  <lastmod>2026-08-27T08:40:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適化としての教師なし画像マッチングとオブジェクト発見（Unsupervised Image Matching and Object Discovery as Optimization）</news:title>
   <news:publication_date>2026-08-27T08:40:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727765</loc>
  <lastmod>2026-08-27T08:38:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間ショートカットネットワークによる姿勢推定の効率化（Spatial Shortcut Network for Human Pose Estimation）</news:title>
   <news:publication_date>2026-08-27T08:38:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727763</loc>
  <lastmod>2026-08-27T08:30:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HomebrewedDB：6D姿勢推定のためのRGB-Dデータセット（HomebrewedDB: RGB-D Dataset for 6D Pose Estimation of 3D Objects）</news:title>
   <news:publication_date>2026-08-27T08:30:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727761</loc>
  <lastmod>2026-08-27T08:30:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散フーリエ変換が分子の電子特性予測を変える（Discrete Fourier Transform Improves the Prediction of the Electronic Properties of Molecules in Quantum Machine Learning）</news:title>
   <news:publication_date>2026-08-27T08:30:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727759</loc>
  <lastmod>2026-08-27T08:29:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>記憶を学習する仕組み：シナプス可塑性に基づく継続学習フレームワーク（Learning to Remember: A Synaptic Plasticity Driven Framework for Continual Learning）</news:title>
   <news:publication_date>2026-08-27T08:29:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727757</loc>
  <lastmod>2026-08-27T08:29:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モンジュ行列の推定（Estimation of Monge Matrices）</news:title>
   <news:publication_date>2026-08-27T08:29:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727755</loc>
  <lastmod>2026-08-27T08:29:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低遅延の教師なし音声強調手法の実装と意義（Unsupervised Low Latency Speech Enhancement with RT-GCC-NMF）</news:title>
   <news:publication_date>2026-08-27T08:29:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727753</loc>
  <lastmod>2026-08-27T07:38:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>べき乗則に適応した確率的ブロックモデル（Adapting Stochastic Block Models to Power-Law Degree Distributions）</news:title>
   <news:publication_date>2026-08-27T07:38:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727751</loc>
  <lastmod>2026-08-27T07:37:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互一貫性を用いた高速な弱教師あり行動分割（Fast Weakly Supervised Action Segmentation Using Mutual Consistency）</news:title>
   <news:publication_date>2026-08-27T07:37:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727749</loc>
  <lastmod>2026-08-27T07:37:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療画像における深層学習の可視化を再定義する手法（Deep Learning Under the Microscope: Improving the Interpretability of Medical Imaging Neural Networks）</news:title>
   <news:publication_date>2026-08-27T07:37:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727747</loc>
  <lastmod>2026-08-27T07:36:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期宇宙における高速ガス流出の発見（Fast Outflows Identified in Early Star-Forming Galaxies at z = 5–6）</news:title>
   <news:publication_date>2026-08-27T07:36:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727745</loc>
  <lastmod>2026-08-27T07:36:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クリックデータからの不確実性を伴う多様な個人化推薦（Diverse personalized recommendations with uncertainty from implicit preference data with the Bayesian Mallows Model）</news:title>
   <news:publication_date>2026-08-27T07:36:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727743</loc>
  <lastmod>2026-08-27T07:36:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル言語モデルを「覗く」ための方法論（Analyzing and Interpreting Neural Networks for NLP）</news:title>
   <news:publication_date>2026-08-27T07:36:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727741</loc>
  <lastmod>2026-08-27T07:36:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報集約によるマルチヘッド注意の改善（Information Aggregation for Multi-Head Attention with Routing-by-Agreement）</news:title>
   <news:publication_date>2026-08-27T07:36:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727739</loc>
  <lastmod>2026-08-27T06:44:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>21-cm観測と暖かい暗黒物質モデル（21-cm observations and warm dark matter models）</news:title>
   <news:publication_date>2026-08-27T06:44:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727737</loc>
  <lastmod>2026-08-27T06:44:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Transformerに再帰性を持たせる設計（Modeling Recurrence for Transformer）</news:title>
   <news:publication_date>2026-08-27T06:44:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727735</loc>
  <lastmod>2026-08-27T06:44:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形ランダム行列モデルの固有値分布（Eigenvalue distribution of some nonlinear models of random matrices）</news:title>
   <news:publication_date>2026-08-27T06:44:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727733</loc>
  <lastmod>2026-08-27T06:43:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話で学ぶCLEARumor：ELMoと畳み込みで噂を見抜く（CLEARumor at SemEval-2019 Task 7: ConvoLving ELMo Against Rumors）</news:title>
   <news:publication_date>2026-08-27T06:43:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727731</loc>
  <lastmod>2026-08-27T06:43:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エネルギー散逸ネットワークによるニューラルネット制御（Controlling Neural Networks via Energy Dissipation）</news:title>
   <news:publication_date>2026-08-27T06:43:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727729</loc>
  <lastmod>2026-08-27T06:43:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>放射線治療の輪郭決定を変える畳み込み型ゲート付きグラフニューラルネットワーク（Radiotherapy Target Contouring with Convolutional Gated Graph Neural Network）</news:title>
   <news:publication_date>2026-08-27T06:43:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727727</loc>
  <lastmod>2026-08-27T06:42:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知数の話者を1モデルで分離する再帰的音声分離（Recursive speech separation for unknown number of speakers）</news:title>
   <news:publication_date>2026-08-27T06:42:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727725</loc>
  <lastmod>2026-08-27T05:51:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソースコードにおける埋め込み表現の文献調査（A Literature Study of Embeddings on Source Code）</news:title>
   <news:publication_date>2026-08-27T05:51:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727723</loc>
  <lastmod>2026-08-27T05:51:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼度の異なる複数情報源を統合する確率的ヒートマップ（Bayesian Heatmaps: Probabilistic Classification with Multiple Unreliable Information Sources）</news:title>
   <news:publication_date>2026-08-27T05:51:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727721</loc>
  <lastmod>2026-08-27T05:50:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散環境における契約的データ共有の概念アーキテクチャ（A Conceptual Architecture for Contractual Data Sharing in a Decentralised Environment）</news:title>
   <news:publication_date>2026-08-27T05:50:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727719</loc>
  <lastmod>2026-08-27T05:50:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像文脈におけるマルチタスク学習のタスク関連性学習（Learning Task Relatedness in Multi-Task Learning for Images in Context）</news:title>
   <news:publication_date>2026-08-27T05:50:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727717</loc>
  <lastmod>2026-08-27T05:49:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コードスメルの転移学習可能性を探る（On the Feasibility of Transfer-learning Code Smells using Deep Learning）</news:title>
   <news:publication_date>2026-08-27T05:49:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727715</loc>
  <lastmod>2026-08-27T05:49:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全データからの定量的システムリスク評価（Quantitative system risk assessment from incomplete data with belief networks and pairwise comparison elicitation）</news:title>
   <news:publication_date>2026-08-27T05:49:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727713</loc>
  <lastmod>2026-08-27T05:49:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イベント発火型学習で通信を賢く減らす（Event-triggered Learning）</news:title>
   <news:publication_date>2026-08-27T05:49:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727711</loc>
  <lastmod>2026-08-27T04:57:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトルモデルと深層学習を組み合わせた頑健なバイノーラル音源定位（Robust Binaural Localization of a Target Sound Source by Combining Spectral Source Models and Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-27T04:57:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727709</loc>
  <lastmod>2026-08-27T04:57:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スクラッチからの計画立案：オフラインモデルとオンラインMCTSの統合（Planning from Scratch: Combining Offline Models and Online Monte-Carlo Tree Search for Planning from Scratch）</news:title>
   <news:publication_date>2026-08-27T04:57:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727707</loc>
  <lastmod>2026-08-27T04:57:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深在環境下における多音源の両耳（バイノーラル）定位にDNNと頭部回転を活用する手法（Exploiting Deep Neural Networks and Head Movements for Robust Binaural Localisation of Multiple Sources in Reverberant Environments）</news:title>
   <news:publication_date>2026-08-27T04:57:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727705</loc>
  <lastmod>2026-08-27T04:56:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関係認識型グローバル注意による人物再認識（Relation-Aware Global Attention for Person Re-identification）</news:title>
   <news:publication_date>2026-08-27T04:56:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727703</loc>
  <lastmod>2026-08-27T04:56:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>どの物を使うべきか — タスク駆動型物体検出（What Object Should I Use? - Task Driven Object Detection）</news:title>
   <news:publication_date>2026-08-27T04:56:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727701</loc>
  <lastmod>2026-08-27T04:56:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動微分と記号微分の同等性（On the Equivalence of Automatic and Symbolic Differentiation）</news:title>
   <news:publication_date>2026-08-27T04:56:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727699</loc>
  <lastmod>2026-08-27T04:56:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>睡眠呼吸障害に関する音響検出のための深層学習特徴（DEEP LEARNING FEATURES FOR ROBUST DETECTION OF ACOUSTIC EVENTS IN SLEEP-DISORDERED BREATHING）</news:title>
   <news:publication_date>2026-08-27T04:56:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727697</loc>
  <lastmod>2026-08-27T04:05:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極値のk-meansクラスタリング（k-means clustering of extremes）</news:title>
   <news:publication_date>2026-08-27T04:05:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727695</loc>
  <lastmod>2026-08-27T04:04:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数測定データのためのトポロジカル分類法（A topological data analysis based classification method for multiple measurements）</news:title>
   <news:publication_date>2026-08-27T04:04:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727693</loc>
  <lastmod>2026-08-27T04:04:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セマンティック属性マッチングネットワーク（Semantic Attribute Matching Networks）</news:title>
   <news:publication_date>2026-08-27T04:04:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727691</loc>
  <lastmod>2026-08-27T04:04:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測下の拡散ネットワークにおけるグラフ学習（Graph Learning over Partially Observed Diffusion Networks: Role of Degree Concentration）</news:title>
   <news:publication_date>2026-08-27T04:04:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727689</loc>
  <lastmod>2026-08-27T04:03:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Logitron：拡張ロジスティック損失に基づくPerceptron拡張分類モデル（Logitron: Perceptron-augmented classification model based on an extended logistic loss function）</news:title>
   <news:publication_date>2026-08-27T04:03:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727687</loc>
  <lastmod>2026-08-27T04:03:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ELMo埋め込みの重み付け最適化──層をどう組み合わせるべきか（Alternative Weighting Schemes for ELMo Embeddings）</news:title>
   <news:publication_date>2026-08-27T04:03:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727685</loc>
  <lastmod>2026-08-27T04:03:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続的に適応するステレオ深度推定の学習（Learning to Adapt for Stereo）</news:title>
   <news:publication_date>2026-08-27T04:03:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727683</loc>
  <lastmod>2026-08-27T03:12:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNNから重み付き有限オートマトンを取り出す手法（Weighted Automata Extraction from Recurrent Neural Networks via Regression on State Spaces）</news:title>
   <news:publication_date>2026-08-27T03:12:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727681</loc>
  <lastmod>2026-08-27T03:12:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中心とスケール予測によるアンカーフリー歩行者・顔検出（Center and Scale Prediction: Anchor-free Approach for Pedestrian and Face Detection）</news:title>
   <news:publication_date>2026-08-27T03:12:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727679</loc>
  <lastmod>2026-08-27T03:11:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次的帰納推論の公理的アプローチ（SECOND-ORDER INDUCTIVE INFERENCE: AN AXIOMATIC APPROACH）</news:title>
   <news:publication_date>2026-08-27T03:11:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727677</loc>
  <lastmod>2026-08-27T03:11:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトルグラフクラスタリングの同時次元・複雑性モデル選択（Simultaneous Dimensionality and Complexity Model Selection for Spectral Graph Clustering）</news:title>
   <news:publication_date>2026-08-27T03:11:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727675</loc>
  <lastmod>2026-08-27T03:11:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分岐型マルチタスクネットワーク：どの層を共有すべきか（Branched Multi-Task Networks: Deciding What Layers To Share）</news:title>
   <news:publication_date>2026-08-27T03:11:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727673</loc>
  <lastmod>2026-08-27T03:11:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラインドデコンボリューション顕微鏡法（Blind Deconvolution Microscopy Using Cycle Consistent CNN with Explicit PSF Layer）</news:title>
   <news:publication_date>2026-08-27T03:11:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727671</loc>
  <lastmod>2026-08-27T03:10:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>仮想コホートのシミュレーションがMCI被験者の認知機能低下予測の精度を向上させる（Simulation of virtual cohorts increases predictive accuracy of cognitive decline in MCI subjects）</news:title>
   <news:publication_date>2026-08-27T03:10:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727669</loc>
  <lastmod>2026-08-27T02:19:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>双方向予測による深層予測型ビデオ圧縮（Deep Predictive Video Compression with Bi-directional Prediction）</news:title>
   <news:publication_date>2026-08-27T02:19:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727667</loc>
  <lastmod>2026-08-27T02:18:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化された銀河形態進化シミュレーションと機械学習（Automated Simulations of Galaxy Morphology Evolution using Deep Learning and Particle Swarm Optimisation）</news:title>
   <news:publication_date>2026-08-27T02:18:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727665</loc>
  <lastmod>2026-08-27T02:17:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>服画像のクロスドメイン検索を深層離散表現でつなぐ（Snap and Find: Deep Discrete Cross-domain Garment Image Retrieval）</news:title>
   <news:publication_date>2026-08-27T02:17:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727663</loc>
  <lastmod>2026-08-27T02:17:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Single-Path NAS：モバイル向け高効率ConvNetを4時間未満で設計する手法（Single-Path NAS: Designing Hardware-Efficient ConvNets in less than 4 Hours）</news:title>
   <news:publication_date>2026-08-27T02:17:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727661</loc>
  <lastmod>2026-08-27T02:16:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平行移動不変攻撃による転移可能な敵対的事例の回避（Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks）</news:title>
   <news:publication_date>2026-08-27T02:16:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727659</loc>
  <lastmod>2026-08-27T02:16:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師あり学習における欠測ラベルのパターン（On missing label patterns in semi-supervised learning）</news:title>
   <news:publication_date>2026-08-27T02:16:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727657</loc>
  <lastmod>2026-08-27T01:24:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Attentionモデルに関する注意深いレビュー（An Attentive Survey of Attention Models）</news:title>
   <news:publication_date>2026-08-27T01:24:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727655</loc>
  <lastmod>2026-08-27T01:24:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mumford‑Shahに基づく深層学習のための損失関数（Mumford-Shah Loss Functional for Image Segmentation with Deep Learning）</news:title>
   <news:publication_date>2026-08-27T01:24:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727653</loc>
  <lastmod>2026-08-27T01:23:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラル遷移モデルで拡張するスケーラブルプランニング（Scalable Planning with Deep Neural Network Learned Transition Models）</news:title>
   <news:publication_date>2026-08-27T01:23:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727651</loc>
  <lastmod>2026-08-27T01:23:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速時空間残差ネットワークによる動画超解像（Fast Spatio-Temporal Residual Network for Video Super-Resolution）</news:title>
   <news:publication_date>2026-08-27T01:23:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727649</loc>
  <lastmod>2026-08-27T01:22:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ライブデータを能動的に検索・学習する手法（Actively Seeking and Learning from Live Data）</news:title>
   <news:publication_date>2026-08-27T01:22:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727647</loc>
  <lastmod>2026-08-27T01:22:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データへの公正な価値付け（Data Shapley: Equitable Valuation of Data for Machine Learning）</news:title>
   <news:publication_date>2026-08-27T01:22:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727645</loc>
  <lastmod>2026-08-27T01:22:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゼロショット顔偽装検知におけるDeep Tree Networkの提案（Deep Tree Learning for Zero-shot Face Anti-Spooﬁng）</news:title>
   <news:publication_date>2026-08-27T01:22:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727643</loc>
  <lastmod>2026-08-27T00:31:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的予測の再較正（Probabilistic Recalibration of Forecasts）</news:title>
   <news:publication_date>2026-08-27T00:31:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727641</loc>
  <lastmod>2026-08-27T00:31:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不合理なリスク知覚を考慮した経路計画（Planning under non-rational perception of uncertain spatial costs）</news:title>
   <news:publication_date>2026-08-27T00:31:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727639</loc>
  <lastmod>2026-08-27T00:30:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>隠れたデータ不均衡を克服する音響イベントのサブ辞書学習（Modelling of Sound Events with Hidden Imbalances Based on Clustering and Separate Sub-Dictionary Learning）</news:title>
   <news:publication_date>2026-08-27T00:30:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727637</loc>
  <lastmod>2026-08-27T00:30:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>材料と構造の同時逆設計を深層学習で実現（Simultaneous inverse-design of material and structure via deep-learning）</news:title>
   <news:publication_date>2026-08-27T00:30:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727635</loc>
  <lastmod>2026-08-27T00:30:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層ごとの不確実性最小化による敵対的入力検知（Minimum Uncertainty Based Detection of Adversaries in Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-27T00:30:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727633</loc>
  <lastmod>2026-08-27T00:30:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超音波イメージングのための深層学習ベース汎用ビームフォーマー（Deep Learning-based Universal Beamformer for Ultrasound Imaging）</news:title>
   <news:publication_date>2026-08-27T00:30:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727631</loc>
  <lastmod>2026-08-27T00:29:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大学教室における物理問題と社会的ネットワーク形成（Physics problems and instructional strategies for developing social networks in university classrooms）</news:title>
   <news:publication_date>2026-08-27T00:29:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727629</loc>
  <lastmod>2026-08-26T23:38:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>何が推定できるか（What can be estimated?）</news:title>
   <news:publication_date>2026-08-26T23:38:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727627</loc>
  <lastmod>2026-08-26T23:29:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種スケールを統合する感情語彙のMulti-View VAE（Combining Sentiment Lexica with a Multi-View Variational Autoencoder）</news:title>
   <news:publication_date>2026-08-26T23:29:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727625</loc>
  <lastmod>2026-08-26T23:29:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電力品質異常の機械学習による分類法（A Machine Learning Based Classification Approach for Power Quality Disturbances Exploiting Higher Order Statistics in the EMD Domain）</news:title>
   <news:publication_date>2026-08-26T23:29:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727623</loc>
  <lastmod>2026-08-26T23:29:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FLightNNsによる軽量量子化ニューラルネットワークの実運用価値（FLightNNs: Lightweight Quantized Deep Neural Networks for Fast and Accurate Inference）</news:title>
   <news:publication_date>2026-08-26T23:29:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727621</loc>
  <lastmod>2026-08-26T23:28:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソースコードの「編集」を学習するニューラルネットワーク（Neural Networks for Modeling Source Code Edits）</news:title>
   <news:publication_date>2026-08-26T23:28:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727619</loc>
  <lastmod>2026-08-26T23:28:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>活性化分布の正則化によるバイナリ化ニューラルネットワークの学習改善（Regularizing Activation Distribution for Training Binarized Deep Networks）</news:title>
   <news:publication_date>2026-08-26T23:28:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727617</loc>
  <lastmod>2026-08-26T23:27:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンスベースのスーパーセットラベル学習に対する正則化アプローチ（A Regularization Approach for Instance-based Superset Label Learning）</news:title>
   <news:publication_date>2026-08-26T23:27:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727615</loc>
  <lastmod>2026-08-26T22:36:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈化埋め込みの教師なしドメイン適応による系列ラベリング改善（Unsupervised Domain Adaptation of Contextualized Embeddings for Sequence Labeling）</news:title>
   <news:publication_date>2026-08-26T22:36:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727613</loc>
  <lastmod>2026-08-26T22:36:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像再構成：スパーシティからデータ適応手法と機械学習へ (Image Reconstruction: From Sparsity to Data-adaptive Methods and Machine Learning)</news:title>
   <news:publication_date>2026-08-26T22:36:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727611</loc>
  <lastmod>2026-08-26T22:34:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層型自己注意ネットワークによるトピックスポッティング（Topic Spotting using Hierarchical Networks with Self Attention）</news:title>
   <news:publication_date>2026-08-26T22:34:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727609</loc>
  <lastmod>2026-08-26T22:34:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情駆動型対話生成（Affect-Driven Dialog Generation）</news:title>
   <news:publication_date>2026-08-26T22:34:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727607</loc>
  <lastmod>2026-08-26T22:34:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Faster R-CNNを用いた人間–機械協調視覚探索の評価（Assessment of Faster R-CNN in Man-Machine collaborative search）</news:title>
   <news:publication_date>2026-08-26T22:34:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727605</loc>
  <lastmod>2026-08-26T22:34:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適ベイズ推論における重なり行列の収束（Overlap matrix concentration in optimal Bayesian inference）</news:title>
   <news:publication_date>2026-08-26T22:34:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727603</loc>
  <lastmod>2026-08-26T22:32:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Amazonレビューの深層感情分析と評価の整合性検出（DEEP LEARNING SENTIMENT ANALYSIS OF AMAZON.COM REVIEWS AND RATINGS）</news:title>
   <news:publication_date>2026-08-26T22:32:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727601</loc>
  <lastmod>2026-08-26T21:41:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間評価と統計評価を統一する指標の提案（Unifying Human and Statistical Evaluation for Natural Language Generation）</news:title>
   <news:publication_date>2026-08-26T21:41:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727599</loc>
  <lastmod>2026-08-26T21:41:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュースキャスター音声を少量データで合成する二様式テキスト読み上げモデル（In Other News: A Bi-style Text-to-speech Model for Synthesizing Newscaster Voice with Limited Data）</news:title>
   <news:publication_date>2026-08-26T21:41:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727597</loc>
  <lastmod>2026-08-26T21:40:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑さ重み付き損失と多様な再ランキングによる文章簡約化（Complexity-Weighted Loss and Diverse Reranking for Sentence Simplification）</news:title>
   <news:publication_date>2026-08-26T21:40:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727595</loc>
  <lastmod>2026-08-26T21:40:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次適応型機械学習の枠組み（Adaptive Sequential Machine Learning）</news:title>
   <news:publication_date>2026-08-26T21:40:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727593</loc>
  <lastmod>2026-08-26T21:40:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意図認識を組み込んだ確率的軌道推定による衝突予測と不確実性定量化（Intent-Aware Probabilistic Trajectory Estimation for Collision Prediction with Uncertainty Quantification）</news:title>
   <news:publication_date>2026-08-26T21:40:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727591</loc>
  <lastmod>2026-08-26T21:40:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>沿岸域の魚類分類におけるCNNとSqueeze‑and‑Excitationの活用（Biometric Fish Classification of Temperate Species Using Convolutional Neural Network with Squeeze-and-Excitation）</news:title>
   <news:publication_date>2026-08-26T21:40:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727589</loc>
  <lastmod>2026-08-26T20:47:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの盲目的視覚モチーフ除去（Blind Visual Motif Removal from a Single Image）</news:title>
   <news:publication_date>2026-08-26T20:47:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727587</loc>
  <lastmod>2026-08-26T20:37:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話スタイル適合を行うエンドツーエンド会話エージェント (An End-to-End Conversational Style Matching Agent)</news:title>
   <news:publication_date>2026-08-26T20:37:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727585</loc>
  <lastmod>2026-08-26T20:37:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Affinityグラフ上で学習する顔クラスタリング（Learning to Cluster Faces on an Affinity Graph）</news:title>
   <news:publication_date>2026-08-26T20:37:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727583</loc>
  <lastmod>2026-08-26T20:35:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一高次テンソルでFCNをパラメータ化するT-Net（T-Net: Parametrizing Fully Convolutional Nets with a Single High-Order Tensor）</news:title>
   <news:publication_date>2026-08-26T20:35:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727581</loc>
  <lastmod>2026-08-26T20:35:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河球状星団における炭素不均一性と深混合速度の普及（Carbon Abundance Inhomogeneities and Deep Mixing Rates in Galactic Globular Clusters）</news:title>
   <news:publication_date>2026-08-26T20:35:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727579</loc>
  <lastmod>2026-08-26T20:35:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習の偏りを正す物体検出の設計―Libra R-CNNの示した均衡化戦略（Libra R-CNN: Towards Balanced Learning for Object Detection）</news:title>
   <news:publication_date>2026-08-26T20:35:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727577</loc>
  <lastmod>2026-08-26T20:34:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による系外惑星同定 III：TESS候補の自動選別と検証（IDENTIFYING EXOPLANETS WITH DEEP LEARNING III: AUTOMATED TRIAGE AND VETTING OF TESS CANDIDATES）</news:title>
   <news:publication_date>2026-08-26T20:34:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727575</loc>
  <lastmod>2026-08-26T19:43:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neural#DNFによる近似DNFカウントの学習的アプローチ（Learning to Reason: Leveraging Neural Networks for Approximate DNF Counting）</news:title>
   <news:publication_date>2026-08-26T19:43:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727573</loc>
  <lastmod>2026-08-26T19:42:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイムなインスタンスセグメンテーション手法YOLACT（YOLACT: Real-time Instance Segmentation）</news:title>
   <news:publication_date>2026-08-26T19:42:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727571</loc>
  <lastmod>2026-08-26T19:42:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Transformerベース言語表現モデルにおけるアテンションの可視化 (Visualizing Attention in Transformer-Based Language Representation Models)</news:title>
   <news:publication_date>2026-08-26T19:42:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727569</loc>
  <lastmod>2026-08-26T19:42:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>被験者クロスバリデーションが示す人体活動認識評価の落とし穴（Subject Cross Validation in Human Activity Recognition）</news:title>
   <news:publication_date>2026-08-26T19:42:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727567</loc>
  <lastmod>2026-08-26T19:42:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からのハイライト除去における多クラス敵対的学習（Deep Multi-class Adversarial Specularity Removal）</news:title>
   <news:publication_date>2026-08-26T19:42:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727565</loc>
  <lastmod>2026-08-26T19:41:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>読み取り理解モデルが易しい例でも学習効果を示さない問題（Frustratingly Poor Performance of Reading Comprehension Models on Non-adversarial Examples）</news:title>
   <news:publication_date>2026-08-26T19:41:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727563</loc>
  <lastmod>2026-08-26T19:41:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitterのプロフィールと投稿画像が示すうつ・不安の指標（What Twitter Profile and Posted Images Reveal About Depression and Anxiety）</news:title>
   <news:publication_date>2026-08-26T19:41:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727561</loc>
  <lastmod>2026-08-26T18:50:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移学習のための取得関数のメタ学習（Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization）</news:title>
   <news:publication_date>2026-08-26T18:50:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727559</loc>
  <lastmod>2026-08-26T18:50:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>双子型エンコーディングによる多段階自己教師付き整列（Siamese Encoding and Alignment by Multiscale Learning with Self-Supervision）</news:title>
   <news:publication_date>2026-08-26T18:50:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727557</loc>
  <lastmod>2026-08-26T18:49:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経験的ベイズ後悔最小化によるバンディット最適化の実務化（Empirical Bayes Regret Minimization）</news:title>
   <news:publication_date>2026-08-26T18:49:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727555</loc>
  <lastmod>2026-08-26T18:49:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正常性を記憶して異常を検知する仕組み（Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection）</news:title>
   <news:publication_date>2026-08-26T18:49:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727553</loc>
  <lastmod>2026-08-26T18:49:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケーラブルなベクター画像の学習表現（A Learned Representation for Scalable Vector Graphics）</news:title>
   <news:publication_date>2026-08-26T18:49:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727551</loc>
  <lastmod>2026-08-26T18:49:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続活動における学習行動の系列解析（Sequence Analysis of Learning Behavior in Different Consecutive Activities）</news:title>
   <news:publication_date>2026-08-26T18:49:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727549</loc>
  <lastmod>2026-08-26T18:48:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床精度の高い胸部X線レポート自動生成（Clinically Accurate Chest X-Ray Report Generation）</news:title>
   <news:publication_date>2026-08-26T18:48:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727547</loc>
  <lastmod>2026-08-26T17:57:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンドの映像キャプショニング（End-to-End Video Captioning）</news:title>
   <news:publication_date>2026-08-26T17:57:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727545</loc>
  <lastmod>2026-08-26T17:57:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信号対雑音比を距離指標にする深層距離学習（Signal-to-Noise Ratio: A Robust Distance Metric for Deep Metric Learning）</news:title>
   <news:publication_date>2026-08-26T17:57:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727543</loc>
  <lastmod>2026-08-26T17:57:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化する自己学習ニューラルネットワーク（Evolving Self-Taught Neural Networks）</news:title>
   <news:publication_date>2026-08-26T17:57:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727541</loc>
  <lastmod>2026-08-26T17:57:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>振動系の動力学を再帰型ニューラルネットワークで推定する（Inferring the dynamics of oscillatory systems using recurrent neural networks）</news:title>
   <news:publication_date>2026-08-26T17:57:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727539</loc>
  <lastmod>2026-08-26T17:56:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間フォノニック結晶と異常なトポロジカルエッジ状態（Space-Time Phononic Crystals with Anomalous Topological Edge States）</news:title>
   <news:publication_date>2026-08-26T17:56:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727537</loc>
  <lastmod>2026-08-26T17:56:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模な種系統樹推定の実務的示唆（Large-scale Species Tree Estimation）</news:title>
   <news:publication_date>2026-08-26T17:56:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727535</loc>
  <lastmod>2026-08-26T17:55:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CADモデルの説明文と名称検出のためのテキスト分類コンポーネント（Text Classification Components for Detecting Descriptions and Names of CAD models）</news:title>
   <news:publication_date>2026-08-26T17:55:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727533</loc>
  <lastmod>2026-08-26T17:04:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈認識自己注意を用いた会話行為分類（Dialogue Act Classification with Context-Aware Self-Attention）</news:title>
   <news:publication_date>2026-08-26T17:04:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727531</loc>
  <lastmod>2026-08-26T17:04:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高温対応深在準位トランジェント分光システム（High-temperature deep-level transient spectroscopy system for defect studies in wide-bandgap semiconductors）</news:title>
   <news:publication_date>2026-08-26T17:04:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727529</loc>
  <lastmod>2026-08-26T17:04:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>代表領域を持つオンライン凸行列分解（Online Convex Matrix Factorization with Representative Regions）</news:title>
   <news:publication_date>2026-08-26T17:04:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727527</loc>
  <lastmod>2026-08-26T17:03:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドローンが映画監督になる日は来るか？（Can a Robot Become a Movie Director? Learning Artistic Principles for Aerial Cinematography）</news:title>
   <news:publication_date>2026-08-26T17:03:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727525</loc>
  <lastmod>2026-08-26T17:03:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>5Gにおけるハンドオーバー最適化を強化する強化学習（5G Handover using Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-26T17:03:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727523</loc>
  <lastmod>2026-08-26T17:03:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DNNシステムの性能モデルに対する転移学習の実用性（Transfer Learning for Performance Modeling of Deep Neural Network Systems）</news:title>
   <news:publication_date>2026-08-26T17:03:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727521</loc>
  <lastmod>2026-08-26T17:02:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeCaFAによる顔ランドマーク整列の統合的アプローチ（DeCaFA: Deep Convolutional Cascade for Face Alignment In The Wild）</news:title>
   <news:publication_date>2026-08-26T17:02:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727519</loc>
  <lastmod>2026-08-26T16:11:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語と脳のエンコーディング評価の堅牢化（Robust Evaluation of Language–Brain Encoding Experiments）</news:title>
   <news:publication_date>2026-08-26T16:11:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727517</loc>
  <lastmod>2026-08-26T16:11:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非整列ネットワークの異質集団におけるコミュニティ検出（Community Detection over a Heterogeneous Population of Non-Aligned Networks）</news:title>
   <news:publication_date>2026-08-26T16:11:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727515</loc>
  <lastmod>2026-08-26T16:11:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多目的最適化によるEEG分類への転移学習（A Many Objective Optimization Approach for Transfer Learning in EEG Classification）</news:title>
   <news:publication_date>2026-08-26T16:11:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727513</loc>
  <lastmod>2026-08-26T16:10:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フランス発・学校向けラーニングアナリティクスの実装戦略（Learning Analytics Made in France: The METAL project）</news:title>
   <news:publication_date>2026-08-26T16:10:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727511</loc>
  <lastmod>2026-08-26T16:09:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ダブルJPEG圧縮の改ざん検出に関する深層マルチスケール識別ネットワーク（Deep Multi-scale Discriminative Networks for Double JPEG Compression Forensics）</news:title>
   <news:publication_date>2026-08-26T16:09:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727509</loc>
  <lastmod>2026-08-26T16:09:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話的オープンエンド物体・アフォーダンス・把持学習（Interactive Open-Ended Object, Affordance and Grasp Learning for Robotic Manipulation）</news:title>
   <news:publication_date>2026-08-26T16:09:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727507</loc>
  <lastmod>2026-08-26T16:09:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的オートエンコーダを再考した教師なし単語翻訳（Revisiting Adversarial Autoencoder for Unsupervised Word Translation）</news:title>
   <news:publication_date>2026-08-26T16:09:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727505</loc>
  <lastmod>2026-08-26T15:17:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>双方向k帰納法による反例学習で探索空間を半減する（Beyond k-induction: Learning from Counterexamples to Bidirectionally Explore the State Space）</news:title>
   <news:publication_date>2026-08-26T15:17:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727503</loc>
  <lastmod>2026-08-26T15:09:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SMURFF：高性能行列因子分解フレームワーク（SMURFF: a High-Performance Framework for Matrix Factorization）</news:title>
   <news:publication_date>2026-08-26T15:09:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727501</loc>
  <lastmod>2026-08-26T15:09:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>決定論的で計算可能なBernstein-von Mises定理（A deterministic and computable Bernstein-von Mises theorem）</news:title>
   <news:publication_date>2026-08-26T15:09:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727499</loc>
  <lastmod>2026-08-26T15:07:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文埋め込みの合成：統計的関係学習からの教訓 (Composition of Sentence Embeddings: Lessons from Statistical Relational Learning)</news:title>
   <news:publication_date>2026-08-26T15:07:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727497</loc>
  <lastmod>2026-08-26T15:07:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予測モデルの事後説明の分類（A Categorisation of Post-hoc Explanations for Predictive Models）</news:title>
   <news:publication_date>2026-08-26T15:07:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727495</loc>
  <lastmod>2026-08-26T15:06:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子コンピュータ上での強化学習によるスピンハミルトニアン問題の自律解法（Neural network agent playing spin Hamiltonian games on a quantum computer）</news:title>
   <news:publication_date>2026-08-26T15:06:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727493</loc>
  <lastmod>2026-08-26T15:06:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二進数の算術を学ぶニューラル・チューリング・マシン（Learning Numeracy: Binary Arithmetic with Neural Turing Machines）</news:title>
   <news:publication_date>2026-08-26T15:06:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727491</loc>
  <lastmod>2026-08-26T14:15:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層共同スペクトル・空間特徴学習と能動転移学習による高分解能ハイパースペクトル画像分類（Active Transfer Learning Network: A Unified Deep Joint Spectral-Spatial Feature Learning Model For Hyperspectral Image Classification）</news:title>
   <news:publication_date>2026-08-26T14:15:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727489</loc>
  <lastmod>2026-08-26T14:15:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェブから学ぶ視線推定の自己教師表現（Unsupervised Learning of Eye Gaze Representation from the Web）</news:title>
   <news:publication_date>2026-08-26T14:15:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727487</loc>
  <lastmod>2026-08-26T14:14:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語埋め込み回帰によるニューラル機械翻訳の正則化（ReWE: Regressing Word Embeddings for Regularization of Neural Machine Translation Systems）</news:title>
   <news:publication_date>2026-08-26T14:14:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727485</loc>
  <lastmod>2026-08-26T14:13:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相関データに対する交差検証の補正（Cross-Validation for Correlated Data）</news:title>
   <news:publication_date>2026-08-26T14:13:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727483</loc>
  <lastmod>2026-08-26T14:13:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルウェア検出における機械学習と深層学習の現状（Malware Detection using Machine Learning and Deep Learning）</news:title>
   <news:publication_date>2026-08-26T14:13:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727481</loc>
  <lastmod>2026-08-26T14:13:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トリプレットに基づく深層ハッシュネットワークによるクロスモーダル検索（Triplet-Based Deep Hashing Network for Cross-Modal Retrieval）</news:title>
   <news:publication_date>2026-08-26T14:13:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727479</loc>
  <lastmod>2026-08-26T14:13:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数例ラベルからの脳セグメンテーション（Few-shot brain segmentation from weakly labeled data with deep heteroscedastic multi-task networks）</news:title>
   <news:publication_date>2026-08-26T14:13:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727477</loc>
  <lastmod>2026-08-26T13:21:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Resource Efficient 3D Convolutional Neural Networks（Resource Efficient 3D Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-26T13:21:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727475</loc>
  <lastmod>2026-08-26T13:21:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散特徴を扱うための効率的なGANベースのサイバー侵入検知手法（Efficient GAN-based method for cyber-intrusion detection）</news:title>
   <news:publication_date>2026-08-26T13:21:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727473</loc>
  <lastmod>2026-08-26T13:21:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>かき混ぜて学ぶ液体特性のオンライン推定（To Stir or Not to Stir: Online Estimation of Liquid Properties for Pouring Actions）</news:title>
   <news:publication_date>2026-08-26T13:21:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727471</loc>
  <lastmod>2026-08-26T13:19:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極限的に限られた情報からの多孔質材料再構成（Accurate and Fast reconstruction of Porous Media from Extremely Limited Information Using Conditional Generative Adversarial Network）</news:title>
   <news:publication_date>2026-08-26T13:19:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727469</loc>
  <lastmod>2026-08-26T13:19:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース連想記憶を用いた転移学習（Transfer Learning with Sparse Associative Memories）</news:title>
   <news:publication_date>2026-08-26T13:19:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727467</loc>
  <lastmod>2026-08-26T13:19:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘイト・シンボルを解読する方法（Learning to Decipher Hate Symbols）</news:title>
   <news:publication_date>2026-08-26T13:19:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727465</loc>
  <lastmod>2026-08-26T13:19:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>White-to-Black による敵対的攻撃の効率的蒸留（White-to-Black: Efficient Distillation of Black-Box Adversarial Attacks）</news:title>
   <news:publication_date>2026-08-26T13:19:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727463</loc>
  <lastmod>2026-08-26T12:27:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Riemannian Normalizing Flowを用いたWasserstein VAEによるテキストモデリング（Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling）</news:title>
   <news:publication_date>2026-08-26T12:27:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727461</loc>
  <lastmod>2026-08-26T12:27:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最少データで学ぶメタ学習のハイブリッド手法（A Hybrid Approach with Optimization and Metric-based Meta-Learner for Few-Shot Learning）</news:title>
   <news:publication_date>2026-08-26T12:27:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727459</loc>
  <lastmod>2026-08-26T12:26:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互作用を考慮したマルチエージェント追跡と確率的行動予測（Interaction-aware Multi-agent Tracking and Probabilistic Behavior Prediction via Adversarial Learning）</news:title>
   <news:publication_date>2026-08-26T12:26:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727457</loc>
  <lastmod>2026-08-26T12:26:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>虚偽情報対策における解釈可能性の可能性（Open Issues in Combating Fake News: Interpretability as an Opportunity）</news:title>
   <news:publication_date>2026-08-26T12:26:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727455</loc>
  <lastmod>2026-08-26T12:26:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非ベイズ的社会学習と不完全な私的信号構造（Non-Bayesian Social Learning with Imperfect Private Signal Structure）</news:title>
   <news:publication_date>2026-08-26T12:26:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727453</loc>
  <lastmod>2026-08-26T12:26:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Point Cloud向け連続畳み込みの提案（ConvPoint: Continuous Convolutions for Point Cloud Processing）</news:title>
   <news:publication_date>2026-08-26T12:26:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727451</loc>
  <lastmod>2026-08-26T12:26:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市環境における伝搬損失予測のための人工ニューラルネットワーク（Artificial Neural Network Modeling for Path Loss Prediction in Urban Environments）</news:title>
   <news:publication_date>2026-08-26T12:26:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727449</loc>
  <lastmod>2026-08-26T11:35:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間畳み込みニューラルネットワークによる映像物体分割（Spatiotemporal CNN for Video Object Segmentation）</news:title>
   <news:publication_date>2026-08-26T11:35:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727447</loc>
  <lastmod>2026-08-26T11:34:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン適応をロバスト学習として解く――現場で使える物体検出器の作り方（A Robust Learning Approach to Domain Adaptive Object Detection）</news:title>
   <news:publication_date>2026-08-26T11:34:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727445</loc>
  <lastmod>2026-08-26T11:34:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンプレートベースの自動探索で小型セグメンテーションを設計する（Template-Based Automatic Search of Compact Semantic Segmentation Architectures）</news:title>
   <news:publication_date>2026-08-26T11:34:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727443</loc>
  <lastmod>2026-08-26T11:33:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープ・バックプロジェクションネットワークによる単一画像超解像（Deep Back-Projection Networks for Single Image Super-resolution）</news:title>
   <news:publication_date>2026-08-26T11:33:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727441</loc>
  <lastmod>2026-08-26T11:33:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>参照語順のゆらぎを許容する微分可能サンプリング（Differentiable Sampling with Flexible Reference Word Order）</news:title>
   <news:publication_date>2026-08-26T11:33:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727439</loc>
  <lastmod>2026-08-26T11:33:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文書レベルのN項関係抽出における多重スケール表現学習（Document-Level N-ary Relation Extraction with Multiscale Representation Learning）</news:title>
   <news:publication_date>2026-08-26T11:33:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727437</loc>
  <lastmod>2026-08-26T11:33:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応重み付き学習で軽量化した単一画像超解像ネットワーク（Lightweight Image Super-Resolution with Adaptive Weighted Learning Network）</news:title>
   <news:publication_date>2026-08-26T11:33:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727435</loc>
  <lastmod>2026-08-26T10:41:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>双言語単語埋め込みの密度整合（Density Matching for Bilingual Word Embedding）</news:title>
   <news:publication_date>2026-08-26T10:41:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727433</loc>
  <lastmod>2026-08-26T10:41:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Preference Neural Networkによるラベルランキングの再定義（Preference Neural Network）</news:title>
   <news:publication_date>2026-08-26T10:41:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727431</loc>
  <lastmod>2026-08-26T10:41:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的環境下における自律車のリスク上限付きオンライン軌道計画（Online Risk-Bounded Motion Planning for Autonomous Vehicles in Dynamic Environments）</news:title>
   <news:publication_date>2026-08-26T10:41:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727429</loc>
  <lastmod>2026-08-26T10:40:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SUMMITによる深層学習の可視化と解釈の大規模化（SUMMIT: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations）</news:title>
   <news:publication_date>2026-08-26T10:40:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727427</loc>
  <lastmod>2026-08-26T10:40:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴ピラミッドによるハッシング（Feature Pyramid Hashing）</news:title>
   <news:publication_date>2026-08-26T10:40:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727425</loc>
  <lastmod>2026-08-26T10:40:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチビュー環境で「欠け」を補う表現学習の新手法（Multi-view Intact Space Learning）</news:title>
   <news:publication_date>2026-08-26T10:40:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727423</loc>
  <lastmod>2026-08-26T10:40:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一貫性に基づくゼロショット機械翻訳（Consistency by Agreement in Zero-shot Neural Machine Translation）</news:title>
   <news:publication_date>2026-08-26T10:40:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727421</loc>
  <lastmod>2026-08-26T09:49:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前学習済みInception-ResNetを用いた修正分布整合によるドメイン適応（Modified Distribution Alignment for Domain Adaptation with Pre-trained Inception ResNet）</news:title>
   <news:publication_date>2026-08-26T09:49:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727419</loc>
  <lastmod>2026-08-26T09:48:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>要約生成をQA報酬で導く手法（Guiding Extractive Summarization with Question-Answering Rewards）</news:title>
   <news:publication_date>2026-08-26T09:48:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727417</loc>
  <lastmod>2026-08-26T09:48:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知環境で動く被写体を追うドローン撮影の自律化（Towards a Robust Aerial Cinematography Platform: Localizing and Tracking Moving Targets in Unstructured Environments）</news:title>
   <news:publication_date>2026-08-26T09:48:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727415</loc>
  <lastmod>2026-08-26T09:47:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木構造上で計算される関数について（ON FUNCTIONS COMPUTED ON TREES）</news:title>
   <news:publication_date>2026-08-26T09:47:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727413</loc>
  <lastmod>2026-08-26T09:47:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブグラフランキングと結合スコアによるシンプル質問応答（Simple Question Answering with Subgraph Ranking and Joint-Scoring）</news:title>
   <news:publication_date>2026-08-26T09:47:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727411</loc>
  <lastmod>2026-08-26T09:47:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般的活性化関数を持つニューラルネットワークの近似率（APPROXIMATION RATES FOR NEURAL NETWORKS WITH GENERAL ACTIVATION FUNCTIONS）</news:title>
   <news:publication_date>2026-08-26T09:47:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727409</loc>
  <lastmod>2026-08-26T09:47:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力変換による推論改善（Improved Inference via Deep Input Transfer）</news:title>
   <news:publication_date>2026-08-26T09:47:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727407</loc>
  <lastmod>2026-08-26T08:54:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>堅牢な深層ガウス過程（Robust Deep Gaussian Processes）</news:title>
   <news:publication_date>2026-08-26T08:54:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727405</loc>
  <lastmod>2026-08-26T08:54:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習不要・ワンショットで地理空間物体を検出する枠組み（A TRAINING-FREE, ONE-SHOT DETECTION FRAMEWORK FOR GEOSPATIAL OBJECTS IN REMOTE SENSING IMAGES）</news:title>
   <news:publication_date>2026-08-26T08:54:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727403</loc>
  <lastmod>2026-08-26T08:54:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラス不均衡を直接扱う特徴選択（Cost-Sensitive Feature Selection by Optimizing F-measures）</news:title>
   <news:publication_date>2026-08-26T08:54:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727401</loc>
  <lastmod>2026-08-26T08:53:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GAN2vecによるテキスト生成（Generative Adversarial Networks for text using word2vec intermediaries）</news:title>
   <news:publication_date>2026-08-26T08:53:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727399</loc>
  <lastmod>2026-08-26T08:53:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gated-GANによる多コレクションスタイル転送の意義（Gated-GAN: Adversarial Gated Networks for Multi-Collection Style Transfer）</news:title>
   <news:publication_date>2026-08-26T08:53:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727397</loc>
  <lastmod>2026-08-26T08:53:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HoloDetect: 少数ショットでデータ誤りを見つける技術（HoloDetect: Few-Shot Learning for Error Detection）</news:title>
   <news:publication_date>2026-08-26T08:53:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727395</loc>
  <lastmod>2026-08-26T08:53:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Sivers効果に対する新しいアプローチ（New approach to the Sivers effect in the collinear twist-3 formalism）</news:title>
   <news:publication_date>2026-08-26T08:53:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727393</loc>
  <lastmod>2026-08-26T08:02:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二重注意型グラフ畳み込みネットワーク（DAGCN: Dual Attention Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-08-26T08:02:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727391</loc>
  <lastmod>2026-08-26T08:02:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形およびカーネル分類器の訓練に対するサブリニア量子アルゴリズム（Sublinear quantum algorithms for training linear and kernel-based classifiers）</news:title>
   <news:publication_date>2026-08-26T08:02:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727389</loc>
  <lastmod>2026-08-26T08:01:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RGB-D画像からの連続直接スパース視覚測程（Continuous Direct Sparse Visual Odometry from RGB-D Images）</news:title>
   <news:publication_date>2026-08-26T08:01:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727387</loc>
  <lastmod>2026-08-26T08:01:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語埋め込みの多クラス偏りを検出・除去する方法（Black is to Criminal as Caucasian is to Police: Detecting and Removing Multiclass Bias in Word Embeddings）</news:title>
   <news:publication_date>2026-08-26T08:01:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727385</loc>
  <lastmod>2026-08-26T08:00:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理法則を組み込むディープラーニング──4D地震データによる圧力・飽和度反転の事例（INCLUDING PHYSICS IN DEEP LEARNING – AN EXAMPLE FROM 4D SEISMIC PRESSURE SATURATION INVERSION）</news:title>
   <news:publication_date>2026-08-26T08:00:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727383</loc>
  <lastmod>2026-08-26T08:00:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>日本語の述語および事象名詞の格構造解析におけるマルチタスク学習（Multi-task Learning for Japanese Predicate Argument Structure Analysis）</news:title>
   <news:publication_date>2026-08-26T08:00:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727381</loc>
  <lastmod>2026-08-26T08:00:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈を越えた学習：会話レベル特徴が比喩識別を改善する（Learning Outside the Box: Discourse-level Features Improve Metaphor Identification）</news:title>
   <news:publication_date>2026-08-26T08:00:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727379</loc>
  <lastmod>2026-08-26T07:08:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生体試料における定量ラマン分光の前処理最適化と機械学習（Optimized Preprocessing and Machine Learning for Quantitative Raman Spectroscopy in Biology）</news:title>
   <news:publication_date>2026-08-26T07:08:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727377</loc>
  <lastmod>2026-08-26T07:08:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーボリック画像埋め込み（Hyperbolic Image Embeddings）</news:title>
   <news:publication_date>2026-08-26T07:08:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727375</loc>
  <lastmod>2026-08-26T07:08:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>熱赤外から可視スペクトルへの未対合変換（Unpaired Thermal to Visible Spectrum Transfer using Adversarial Training）</news:title>
   <news:publication_date>2026-08-26T07:08:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727373</loc>
  <lastmod>2026-08-26T07:07:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>雑然とした環境での物理ベース把持学習（Learning Physics-Based Manipulation in Clutter）</news:title>
   <news:publication_date>2026-08-26T07:07:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727371</loc>
  <lastmod>2026-08-26T07:06:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>下流の分類タスクが文埋め込み評価に与える影響（The Effect of Downstream Classification Tasks for Evaluating Sentence Embeddings）</news:title>
   <news:publication_date>2026-08-26T07:06:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727369</loc>
  <lastmod>2026-08-26T07:06:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロバストなマルチエージェント反事実予測（Robust Multi-agent Counterfactual Prediction）</news:title>
   <news:publication_date>2026-08-26T07:06:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727367</loc>
  <lastmod>2026-08-26T07:06:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的グラウンディングの再検討（Revisiting Visual Grounding）</news:title>
   <news:publication_date>2026-08-26T07:06:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727365</loc>
  <lastmod>2026-08-26T06:14:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DFANetによる高速語義セグメンテーションの実用化可能性（DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentation）</news:title>
   <news:publication_date>2026-08-26T06:14:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727363</loc>
  <lastmod>2026-08-26T06:14:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>温度時系列の分解を非負値行列因子分解で行う意義（Decomposing Temperature Time Series with Non-Negative Matrix Factorization）</news:title>
   <news:publication_date>2026-08-26T06:14:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727361</loc>
  <lastmod>2026-08-26T06:14:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Ising Born Machineによる生成モデルの量子優位性の提示（The Born Supremacy: Quantum Advantage and Training of an Ising Born Machine）</news:title>
   <news:publication_date>2026-08-26T06:14:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727359</loc>
  <lastmod>2026-08-26T06:13:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共有道路上の人間行動を学習し操る方法（The Green Choice: Learning and Influencing Human Decisions on Shared Roads）</news:title>
   <news:publication_date>2026-08-26T06:13:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727357</loc>
  <lastmod>2026-08-26T06:13:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大量多言語に対する敵対的音声認識の研究（Massively Multilingual Adversarial Speech Recognition）</news:title>
   <news:publication_date>2026-08-26T06:13:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727355</loc>
  <lastmod>2026-08-26T06:13:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師付き・自己符号化器・価値損失を共同で事前学習する手法（JOINTLY PRE-TRAINING WITH SUPERVISED, AUTOENCODER, AND VALUE LOSSES FOR DEEP REINFORCEMENT LEARNING）</news:title>
   <news:publication_date>2026-08-26T06:13:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727353</loc>
  <lastmod>2026-08-26T06:12:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>漸進的確率的2値化による深層ネットワークの効率化（Progressive Stochastic Binarization of Deep Networks）</news:title>
   <news:publication_date>2026-08-26T06:12:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727351</loc>
  <lastmod>2026-08-26T05:20:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味を意識した画像間翻訳とドメイン転移（Semantics-Aware Image to Image Translation and Domain Transfer）</news:title>
   <news:publication_date>2026-08-26T05:20:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727349</loc>
  <lastmod>2026-08-26T05:20:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PaintBotによる自然画材のための強化学習アプローチ（PaintBot: A Reinforcement Learning Approach for Natural Media Painting）</news:title>
   <news:publication_date>2026-08-26T05:20:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727347</loc>
  <lastmod>2026-08-26T05:19:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D Bird’s-Eye-Viewによる点群のインスタンスセグメンテーション（3D Bird’s-Eye-View Instance Segmentation）</news:title>
   <news:publication_date>2026-08-26T05:19:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727345</loc>
  <lastmod>2026-08-26T05:19:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低深度光学ニューラルネットワーク（Low-Depth Optical Neural Networks）</news:title>
   <news:publication_date>2026-08-26T05:19:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727343</loc>
  <lastmod>2026-08-26T05:19:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子カルテを使った医療機器監視（Medical device surveillance with electronic health records）</news:title>
   <news:publication_date>2026-08-26T05:19:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727341</loc>
  <lastmod>2026-08-26T05:19:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CloudCAMPによるクラウドサービス展開の自動化（CloudCAMP: Automating Cloud Services Deployment &amp;amp; Management）</news:title>
   <news:publication_date>2026-08-26T05:19:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727339</loc>
  <lastmod>2026-08-26T05:18:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルウェア検出におけるコンピュータビジョンの有効性・信頼性・回復力（Understanding the efficacy, reliability and resiliency of computer vision techniques for malware detection and future research directions）</news:title>
   <news:publication_date>2026-08-26T05:18:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727337</loc>
  <lastmod>2026-08-26T04:27:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>決定ベースのクエリ効率化手法 HopSkipJumpAttack（HopSkipJumpAttack: A Query-Efficient Decision-Based Attack）</news:title>
   <news:publication_date>2026-08-26T04:27:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727335</loc>
  <lastmod>2026-08-26T04:27:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話的画像生成のための制約付きGAN（Constrained Generative Adversarial Networks for Interactive Image Generation）</news:title>
   <news:publication_date>2026-08-26T04:27:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727333</loc>
  <lastmod>2026-08-26T04:26:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし潜在木構造誘導と深層インサイド・アウトサイド再帰オートエンコーダ（Unsupervised Latent Tree Induction with Deep Inside-Outside Recursive Autoencoders）</news:title>
   <news:publication_date>2026-08-26T04:26:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727331</loc>
  <lastmod>2026-08-26T04:26:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>権限で分けて精度を上げるAndroidマルウェア検知（Group-wise classification approach to improve Android malicious apps detection accuracy）</news:title>
   <news:publication_date>2026-08-26T04:26:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727329</loc>
  <lastmod>2026-08-26T04:25:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CMB偏光レンズと銀河弱視の相関の証拠（Evidence for the Cross-correlation between Cosmic Microwave Background Polarization Lensing from Polarbear and Cosmic Shear from Subaru Hyper Suprime-Cam）</news:title>
   <news:publication_date>2026-08-26T04:25:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727327</loc>
  <lastmod>2026-08-26T04:25:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群の過分割を学習で解く――グラフ構造化深層距離学習による新アプローチ（Point Cloud Oversegmentation with Graph-Structured Deep Metric Learning）</news:title>
   <news:publication_date>2026-08-26T04:25:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727325</loc>
  <lastmod>2026-08-26T04:25:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的勾配降下法に対する正規近似の非漸近収束率（Normal Approximation for Stochastic Gradient Descent via Non-Asymptotic Rates of Martingale CLT）</news:title>
   <news:publication_date>2026-08-26T04:25:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727323</loc>
  <lastmod>2026-08-26T03:34:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デイビス洞窟におけるガンマ線背景測定（Measurement of the Gamma Ray Background in the Davis Cavern at the Sanford Underground Research Facility）</news:title>
   <news:publication_date>2026-08-26T03:34:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727321</loc>
  <lastmod>2026-08-26T03:34:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>75言語を1モデルで解析する手法の要点（75 Languages, 1 Model: Parsing Universal Dependencies Universally）</news:title>
   <news:publication_date>2026-08-26T03:34:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727319</loc>
  <lastmod>2026-08-26T03:33:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療におけるメディカル・デコンファウンダー（The Medical Deconfounder: Assessing Treatment Effects with Electronic Health Records）</news:title>
   <news:publication_date>2026-08-26T03:33:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727317</loc>
  <lastmod>2026-08-26T03:32:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二つの突起ジェットを解釈可能に分類する深層学習（Interpretable Deep Learning for Two-Prong Jet Classification with Jet Spectra）</news:title>
   <news:publication_date>2026-08-26T03:32:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727315</loc>
  <lastmod>2026-08-26T03:32:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>腹部Dixon MRIにおける脂肪組織セグメンテーションのための自動化深層学習パイプライン（FatSegNet: A Fully Automated Deep Learning Pipeline for Adipose Tissue Segmentation on Abdominal Dixon MRI）</news:title>
   <news:publication_date>2026-08-26T03:32:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727313</loc>
  <lastmod>2026-08-26T03:32:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電磁波サイドチャネル解析を使ったIoT機器の鑑識調査（Leveraging Electromagnetic Side-Channel Analysis for the Investigation of IoT Devices）</news:title>
   <news:publication_date>2026-08-26T03:32:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727311</loc>
  <lastmod>2026-08-26T03:32:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手術ビデオの自動整列（Automatic alignment of surgical videos using kinematic data）</news:title>
   <news:publication_date>2026-08-26T03:32:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727309</loc>
  <lastmod>2026-08-26T02:40:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小体積トピックモデリング（Minimum Volume Topic Modeling）</news:title>
   <news:publication_date>2026-08-26T02:40:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727307</loc>
  <lastmod>2026-08-26T02:36:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数種のサブスペースを学習で扱う（Learning for Multi-Type Subspace Clustering）</news:title>
   <news:publication_date>2026-08-26T02:36:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727305</loc>
  <lastmod>2026-08-26T02:36:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitterを使ったサイバー脅威可視化のストリーミング手法（Processing Tweets for Cybersecurity Threat Awareness）</news:title>
   <news:publication_date>2026-08-26T02:36:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727303</loc>
  <lastmod>2026-08-26T02:35:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>健康と親族関係が重要である（Health and Kinship Matter: Learning About Direct-To-Consumer Genetic Testing User Experiences via Online Discussions）</news:title>
   <news:publication_date>2026-08-26T02:35:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727301</loc>
  <lastmod>2026-08-26T02:34:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆型低増幅アバランシェ検出器の意義（Inverse Low Gain Avalanche Detectors (iLGADs) for precise tracking and timing applications）</news:title>
   <news:publication_date>2026-08-26T02:34:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727299</loc>
  <lastmod>2026-08-26T02:34:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>希薄なTwitter空間における薬物乱用検出のためのアンサンブル深層学習モデル（An Ensemble Deep Learning Model for Drug Abuse Detection in Sparse Twitter-Sphere）</news:title>
   <news:publication_date>2026-08-26T02:34:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727297</loc>
  <lastmod>2026-08-26T02:34:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化変分推論：新たな事後分布設計のための三つの論点（Generalized Variational Inference: Three arguments for deriving new Posteriors）</news:title>
   <news:publication_date>2026-08-26T02:34:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727295</loc>
  <lastmod>2026-08-26T01:42:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルベース遺伝的プログラミングの改善と象徴回帰への応用（Improving Model-based Genetic Programming for Symbolic Regression of Small Expressions）</news:title>
   <news:publication_date>2026-08-26T01:42:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727293</loc>
  <lastmod>2026-08-26T01:42:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内陸水域のクロロフィルa推定におけるハイパースペクトルと機械学習の組合せ（Estimating Chlorophyll a Concentrations of Several Inland Waters with Hyperspectral Data and Machine Learning Models）</news:title>
   <news:publication_date>2026-08-26T01:42:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727291</loc>
  <lastmod>2026-08-26T01:41:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンザフライ学習で原子スケールの希少事象を効率的に扱う（On-the-Fly Active Learning of Interpretable Bayesian Force Fields for Atomistic Rare Events）</news:title>
   <news:publication_date>2026-08-26T01:41:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727289</loc>
  <lastmod>2026-08-26T01:40:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>KGR10コーパスを用いたポーランド語単語埋め込みによる時間表現認識の評価（Evaluating KGR10 Polish word embeddings in the recognition of temporal expressions using BiLSTM-CRF）</news:title>
   <news:publication_date>2026-08-26T01:40:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727287</loc>
  <lastmod>2026-08-26T01:40:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機密を守る大規模近傍探索の実装（SANNS: Scaling Up Secure Approximate k-Nearest Neighbors Search）</news:title>
   <news:publication_date>2026-08-26T01:40:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727285</loc>
  <lastmod>2026-08-26T01:40:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OpBergによる因果文検出（OpBerg: Discovering causal sentences using optimal alignments）</news:title>
   <news:publication_date>2026-08-26T01:40:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727283</loc>
  <lastmod>2026-08-26T01:39:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カメラ内パラメータを考慮する単眼深度推定（CAM-Convs: Camera-Aware Multi-Scale Convolutions for Single-View Depth）</news:title>
   <news:publication_date>2026-08-26T01:39:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727281</loc>
  <lastmod>2026-08-26T00:48:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインで進化する特徴学習の新潮流 — STAMによる無監督逐次学習の提案（Unsupervised Progressive Learning and the STAM Architecture）</news:title>
   <news:publication_date>2026-08-26T00:48:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727279</loc>
  <lastmod>2026-08-26T00:47:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文書からの抽出と圧縮を同時に行う要約モデル（Jointly Extracting and Compressing Documents with Summary State Representations）</news:title>
   <news:publication_date>2026-08-26T00:47:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727277</loc>
  <lastmod>2026-08-26T00:47:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不変性が鍵となる人物再識別——ターゲット内変動を記憶するメモリの提案（Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification）</news:title>
   <news:publication_date>2026-08-26T00:47:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727275</loc>
  <lastmod>2026-08-26T00:46:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語内コードスイッチングのサブワード識別（Subword-Level Language Identification for Intra-Word Code-Switching）</news:title>
   <news:publication_date>2026-08-26T00:46:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727273</loc>
  <lastmod>2026-08-26T00:46:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衛星画像から得る深層ランドスケープ特徴による媒介性疾病予測の改善（Deep Landscape Features for Improving Vector-borne Disease Prediction）</news:title>
   <news:publication_date>2026-08-26T00:46:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727271</loc>
  <lastmod>2026-08-26T00:46:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>辺情報を取り込む確率的ブロックモデル（Stochastic Blockmodels with Edge Information）</news:title>
   <news:publication_date>2026-08-26T00:46:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727269</loc>
  <lastmod>2026-08-25T23:54:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HSTが解像したDDO 68に落ち込む小天体の星々（HST resolves stars in a tiny body falling on the dwarf galaxy DDO 68）</news:title>
   <news:publication_date>2026-08-25T23:54:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727267</loc>
  <lastmod>2026-08-25T23:53:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高コントラスト高強度フェムト秒レーザーパルスとシリコン標的の相互作用における強い逆向き衝撃波の生成 (Generation of a strong reverse shock wave in the interaction of a high-contrast high-intensity femtosecond laser pulse with a silicon target)</news:title>
   <news:publication_date>2026-08-25T23:53:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727265</loc>
  <lastmod>2026-08-25T23:53:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一つのニューロンで十分だった：アフタースホック予測における深層学習の過剰性（One neuron is more informative than a deep neural network for aftershock pattern forecasting）</news:title>
   <news:publication_date>2026-08-25T23:53:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727263</loc>
  <lastmod>2026-08-25T23:53:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>D2-Cityに学ぶ実走行ダッシュカム動画データセット（D2-City: A Large-Scale Dashcam Video Dataset of Diverse Traffic Scenarios）</news:title>
   <news:publication_date>2026-08-25T23:53:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727261</loc>
  <lastmod>2026-08-25T23:53:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Rep the Set: 集合表現を学習するニューラルネットワーク（Rep the Set: Neural Networks for Learning Set Representations）</news:title>
   <news:publication_date>2026-08-25T23:53:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727259</loc>
  <lastmod>2026-08-25T23:52:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文字領域認識に基づくシーンテキスト検出（Character Region Awareness for Text Detection）</news:title>
   <news:publication_date>2026-08-25T23:52:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727257</loc>
  <lastmod>2026-08-25T23:52:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>常識推論のための教師なし深層構造意味モデル（Unsupervised Deep Structured Semantic Models for Commonsense Reasoning）</news:title>
   <news:publication_date>2026-08-25T23:52:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727255</loc>
  <lastmod>2026-08-25T23:01:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビッグデータと深層学習の時代における不確実性下の最適化（Optimization under Uncertainty in the Era of Big Data and Deep Learning: When Machine Learning Meets Mathematical Programming）</news:title>
   <news:publication_date>2026-08-25T23:01:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727253</loc>
  <lastmod>2026-08-25T23:01:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>産業4.0における入力変数範囲の決定（Determining input variable ranges in Industry 4.0: A heuristic for estimating the domain of a real-valued function or trained regression model given an output range）</news:title>
   <news:publication_date>2026-08-25T23:01:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727251</loc>
  <lastmod>2026-08-25T23:01:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生波形からのエンドツーエンド二耳定位（End-to-End Binaural Sound Localisation from the Raw Waveform）</news:title>
   <news:publication_date>2026-08-25T23:01:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727249</loc>
  <lastmod>2026-08-25T23:00:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーンテキスト認識研究の比較はどこが問題か（What Is Wrong With Scene Text Recognition Model Comparisons?）</news:title>
   <news:publication_date>2026-08-25T23:00:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727247</loc>
  <lastmod>2026-08-25T23:00:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能で制御可能な顔の再演（Interpretable and Controllable Face Reenactment Using GANs）</news:title>
   <news:publication_date>2026-08-25T23:00:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727245</loc>
  <lastmod>2026-08-25T23:00:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トラッキングを超えて：Deep Visual Odometryのためのメモリ選択と姿勢改善（Beyond Tracking: Selecting Memory and Refining Poses for Deep Visual Odometry）</news:title>
   <news:publication_date>2026-08-25T23:00:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727243</loc>
  <lastmod>2026-08-25T23:00:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層ラベルを活かすセマンティック双線形プーリング（Semantic Bilinear Pooling for Fine-Grained Recognition）</news:title>
   <news:publication_date>2026-08-25T23:00:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727241</loc>
  <lastmod>2026-08-25T22:08:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模コード学習の語彙設計（Modeling Vocabulary for Big Code Machine Learning）</news:title>
   <news:publication_date>2026-08-25T22:08:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727239</loc>
  <lastmod>2026-08-25T22:08:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単調ゲームにおけるナッシュ均衡の学習（Learning Nash Equilibria in Monotone Games）</news:title>
   <news:publication_date>2026-08-25T22:08:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727237</loc>
  <lastmod>2026-08-25T22:08:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幾何認識を取り入れた対称的ドメイン適応による単眼深度推定（Geometry-Aware Symmetric Domain Adaptation for Monocular Depth Estimation）</news:title>
   <news:publication_date>2026-08-25T22:08:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727235</loc>
  <lastmod>2026-08-25T22:07:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ミラーディセントの確率解釈とリスク感受性最適性 (A Stochastic Interpretation of Stochastic Mirror Descent: Risk-Sensitive Optimality)</news:title>
   <news:publication_date>2026-08-25T22:07:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727233</loc>
  <lastmod>2026-08-25T22:07:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴蒸留の包括的再設計（A Comprehensive Overhaul of Feature Distillation）</news:title>
   <news:publication_date>2026-08-25T22:07:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727231</loc>
  <lastmod>2026-08-25T22:07:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一デモから学ぶ接触重視タスクの自己評価学習（Self-Evaluation in One-Shot Learning from Demonstration of Contact-Intensive Task）</news:title>
   <news:publication_date>2026-08-25T22:07:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727229</loc>
  <lastmod>2026-08-25T22:06:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時変因果ネットワークのオンライン同定（Online Topology Identification from Vector Autoregressive Time Series）</news:title>
   <news:publication_date>2026-08-25T22:06:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727227</loc>
  <lastmod>2026-08-25T21:15:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルスライシングによる弾力的推論コスト下での複雑解析支援（Model Slicing for Supporting Complex Analytics with Elastic Inference Cost and Resource Constraints）</news:title>
   <news:publication_date>2026-08-25T21:15:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727225</loc>
  <lastmod>2026-08-25T21:15:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人物検索のためのコンテキストグラフ学習（Learning Context Graph for Person Search）</news:title>
   <news:publication_date>2026-08-25T21:15:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727223</loc>
  <lastmod>2026-08-25T21:14:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし深層トラッキング（Unsupervised Deep Tracking）</news:title>
   <news:publication_date>2026-08-25T21:14:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727221</loc>
  <lastmod>2026-08-25T21:14:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フーリエ位相回復における拡張サポート推定を用いた深層ニューラルネットワーク（Fourier Phase Retrieval with Extended Support Estimation via Deep Neural Network）</news:title>
   <news:publication_date>2026-08-25T21:14:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727219</loc>
  <lastmod>2026-08-25T21:13:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回転不変性を備えた深層ニューラルネットの近似と学習（Deep Neural Networks for Rotation-Invariance Approximation and Learning）</news:title>
   <news:publication_date>2026-08-25T21:13:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727217</loc>
  <lastmod>2026-08-25T21:13:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体認識に基づくセマンティック対応の学習（SFNet: Learning Object-aware Semantic Correspondence）</news:title>
   <news:publication_date>2026-08-25T21:13:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727215</loc>
  <lastmod>2026-08-25T21:13:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスリンガル転移学習による音声言語理解の効率化（CROSS-LINGUAL TRANSFER LEARNING FOR SPOKEN LANGUAGE UNDERSTANDING）</news:title>
   <news:publication_date>2026-08-25T21:13:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727213</loc>
  <lastmod>2026-08-25T20:22:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予算内での深層強化学習：3D制御と推論をスパコンなしで（Deep Reinforcement Learning on a Budget: 3D Control and Reasoning Without a Supercomputer）</news:title>
   <news:publication_date>2026-08-25T20:22:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727211</loc>
  <lastmod>2026-08-25T20:20:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>埋め込み空間での相関を用いた知識蒸留（Correlation Congruence for Knowledge Distillation）</news:title>
   <news:publication_date>2026-08-25T20:20:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727209</loc>
  <lastmod>2026-08-25T20:20:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個人の嗜好を考慮した公正性（Preference-Informed Fairness）</news:title>
   <news:publication_date>2026-08-25T20:20:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727207</loc>
  <lastmod>2026-08-25T20:20:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MAVNet：マイクロ無人機向けセマンティックセグメンテーションの軽量ネットワーク（MAVNet: an Effective Semantic Segmentation Micro-Network for MAV-based Tasks）</news:title>
   <news:publication_date>2026-08-25T20:20:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727205</loc>
  <lastmod>2026-08-25T20:19:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NECにランダム射影を組み込む意味（Random Projection in Neural Episodic Control）</news:title>
   <news:publication_date>2026-08-25T20:19:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727203</loc>
  <lastmod>2026-08-25T19:27:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Soft Rasterizerによる画像ベースの3D推論（Soft Rasterizer: A Differentiable Renderer for Image-based 3D Reasoning）</news:title>
   <news:publication_date>2026-08-25T19:27:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727201</loc>
  <lastmod>2026-08-25T19:27:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き敵対的生成フローによる制御可能な画像合成（Conditional Adversarial Generative Flow for Controllable Image Synthesis）</news:title>
   <news:publication_date>2026-08-25T19:27:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727199</loc>
  <lastmod>2026-08-25T19:26:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中国語の語用誤り検出におけるマルチタスク学習の実務的意義（Multi-task Learning for Chinese Word Usage Errors Detection）</news:title>
   <news:publication_date>2026-08-25T19:26:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727197</loc>
  <lastmod>2026-08-25T19:26:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少量データからの高品質画像生成（Image Generation From Small Datasets via Batch Statistics Adaptation）</news:title>
   <news:publication_date>2026-08-25T19:26:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727195</loc>
  <lastmod>2026-08-25T19:26:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>広告の感情認識と計算広告への応用（Recognition of Advertisement Emotions with Application to Computational Advertising）</news:title>
   <news:publication_date>2026-08-25T19:26:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727193</loc>
  <lastmod>2026-08-25T19:26:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層マルチセット相関解析によるマルチモーダル表現学習（MULTIMODAL REPRESENTATION LEARNING USING DEEP MULTISET CANONICAL CORRELATION ANALYSIS）</news:title>
   <news:publication_date>2026-08-25T19:26:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727191</loc>
  <lastmod>2026-08-25T18:34:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ターゲット認識を意識した深層追跡（Target-Aware Deep Tracking）</news:title>
   <news:publication_date>2026-08-25T18:34:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727189</loc>
  <lastmod>2026-08-25T18:33:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M2KDによる漸進学習の改良（M2KD: Incremental Learning via Multi-model and Multi-level Knowledge Distillation）</news:title>
   <news:publication_date>2026-08-25T18:33:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727187</loc>
  <lastmod>2026-08-25T18:33:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像と言語を同時に学ぶVideoBERTの衝撃（VideoBERT: A Joint Model for Video and Language Representation Learning）</news:title>
   <news:publication_date>2026-08-25T18:33:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727185</loc>
  <lastmod>2026-08-25T18:32:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リーマン運動方策によるニューラル自律航行（Neural Autonomous Navigation with Riemannian Motion Policy）</news:title>
   <news:publication_date>2026-08-25T18:32:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727183</loc>
  <lastmod>2026-08-25T18:32:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチ化された多腕バンディット問題（Batched Multi-armed Bandits Problem）</news:title>
   <news:publication_date>2026-08-25T18:32:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727181</loc>
  <lastmod>2026-08-25T18:32:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で原子単位の量子コンピュータ配列を特定する（Atomic-level Characterisation of Quantum Computer Arrays by Machine Learning）</news:title>
   <news:publication_date>2026-08-25T18:32:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727179</loc>
  <lastmod>2026-08-25T18:32:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスエントロピー敵対的ビュー適応による人物再識別（Cross-Entropy Adversarial View Adaptation for Person Re-identification）</news:title>
   <news:publication_date>2026-08-25T18:32:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727177</loc>
  <lastmod>2026-08-25T17:40:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Styler: Checkstyle違反を学習で自動修正する手法（Styler: learning formatting conventions to repair Checkstyle violations）</news:title>
   <news:publication_date>2026-08-25T17:40:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727175</loc>
  <lastmod>2026-08-25T17:40:47Z</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k-PCAの指数収束を示したMatrix Krasulina（Exponentially convergent stochastic k-PCA without variance reduction）</news:title>
   <news:publication_date>2026-08-25T17:40:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727173</loc>
  <lastmod>2026-08-25T17:40:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク間の関係性を同時に学ぶ新しいマルチタスク学習（On Better Exploring and Exploiting Task Relationships in Multi-Task Learning: Joint Model and Feature Learning）</news:title>
   <news:publication_date>2026-08-25T17:40:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727171</loc>
  <lastmod>2026-08-25T17:40:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SADIH: セマンティック認識型離散ハッシング（SADIH: Semantic-Aware DIscrete Hashing）</news:title>
   <news:publication_date>2026-08-25T17:40:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727169</loc>
  <lastmod>2026-08-25T17:40:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルECにおける短い商品タイトル生成のためのマルチモーダル生成敵対ネットワーク（Multi-Modal Generative Adversarial Network for Short Product Title Generation in Mobile E-Commerce）</news:title>
   <news:publication_date>2026-08-25T17:40:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727167</loc>
  <lastmod>2026-08-25T17:39:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己組織化型マルチエージェントシステムの検証法（Testing Self-Organizing Multiagent Systems）</news:title>
   <news:publication_date>2026-08-25T17:39:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727165</loc>
  <lastmod>2026-08-25T17:39:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔写真の「使える度」を数値化するFaceQnet（FaceQnet: Quality Assessment for Face Recognition based on Deep Learning）</news:title>
   <news:publication_date>2026-08-25T17:39:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727163</loc>
  <lastmod>2026-08-25T16:48:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>StratumによるMLワークフロー運用の自動化（Stratum: A Serverless Framework for the Lifecycle Management of Machine Learning-based Data Analytics Tasks）</news:title>
   <news:publication_date>2026-08-25T16:48:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727152</loc>
  <lastmod>2026-08-25T16:38:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リストワイズ監視を用いた深層ポリシーハッシングネットワーク（Deep Policy Hashing Network with Listwise Supervision）</news:title>
   <news:publication_date>2026-08-25T16:38:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727150</loc>
  <lastmod>2026-08-25T16:37:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>法務文書レビューにおけるテキスト分類の深層学習に関する実証研究 (Empirical Study of Deep Learning for Text Classification in Legal Document Review)</news:title>
   <news:publication_date>2026-08-25T16:37:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727148</loc>
  <lastmod>2026-08-25T16:37:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特権文書レビューにおける機械学習とキーワード検索の比較（An Empirical Study of the Application of Machine Learning and Keyword Terms Methodologies to Privilege-Document Review Projects in Legal Matters）</news:title>
   <news:publication_date>2026-08-25T16:37:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727146</loc>
  <lastmod>2026-08-25T16:37:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>法的文書レビューにおける能動学習戦略の実証的評価 (Empirical Evaluations of Active Learning Strategies in Legal Document Review)</news:title>
   <news:publication_date>2026-08-25T16:37:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727144</loc>
  <lastmod>2026-08-25T16:36:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プログラム自動修復における位置特定と修復の同時学習（NEURAL PROGRAM REPAIR BY JOINTLY LEARNING TO LOCALIZE AND REPAIR）</news:title>
   <news:publication_date>2026-08-25T16:36:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727142</loc>
  <lastmod>2026-08-25T16:36:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前処理設定が予測コーディングの成果を左右する（Empirical Evaluations of Preprocessing Parameters’ Impact on Predictive Coding’s Effectiveness）</news:title>
   <news:publication_date>2026-08-25T16:36:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727140</loc>
  <lastmod>2026-08-25T15:45:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>環境変化下で自律学習する可塑性の進化（Evolving Plasticity for Autonomous Learning under Changing Environmental Conditions）</news:title>
   <news:publication_date>2026-08-25T15:45:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727138</loc>
  <lastmod>2026-08-25T15:36:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DATA Labによる物理実験教育の再設計（Design, Analysis, Tools, and Apprenticeship (DATA) Lab）</news:title>
   <news:publication_date>2026-08-25T15:36:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727136</loc>
  <lastmod>2026-08-25T15:35:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の力学と構成則を学習するPhysics-Informedニューラルネットワークの比較研究 (A comparative study of physics-informed neural network models for learning unknown dynamics and constitutive relations)</news:title>
   <news:publication_date>2026-08-25T15:35:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727134</loc>
  <lastmod>2026-08-25T15:34:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合信号ニューラルネットワークのノイズ耐性向上（Improving Noise Tolerance of Mixed-Signal Neural Networks）</news:title>
   <news:publication_date>2026-08-25T15:34:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727132</loc>
  <lastmod>2026-08-25T15:34:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D点対応の深層登録を同時に解く3DRegNet（3DRegNet: A Deep Neural Network for 3D Point Registration）</news:title>
   <news:publication_date>2026-08-25T15:34:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727130</loc>
  <lastmod>2026-08-25T15:33:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPU向け畳み込みニューラルネットワークのメモリ挙動を正確に予測するモデル（DeLTA: GPU Performance Model for Deep Learning Applications with In-depth Memory System Traffic Analysis）</news:title>
   <news:publication_date>2026-08-25T15:33:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727128</loc>
  <lastmod>2026-08-25T15:33:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチグリッド予測フィルタフローによる教師なし動画学習（Multigrid Predictive Filter Flow for Unsupervised Learning on Videos）</news:title>
   <news:publication_date>2026-08-25T15:33:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
</urlset>