<?xml version="1.0" encoding="UTF-8"?>
<!--generator='jetpack-15.9-a.1'-->
<!--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/691039</loc>
  <lastmod>2026-05-17T02:41:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス線形回帰の効率的サンプリング手法（Efficient sampling for Gaussian linear regression with arbitrary priors）</news:title>
   <news:publication_date>2026-05-17T02:41:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691037</loc>
  <lastmod>2026-05-17T02:41:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーソナライズされたコンテキスト対応ポイント・オブ・インタレスト推薦（Personalized Context-Aware Point of Interest Recommendation）</news:title>
   <news:publication_date>2026-05-17T02:41:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691035</loc>
  <lastmod>2026-05-17T02:41:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>和集合・対称差の集合族に関するSauer–Shelah–Perles型補題（A Sauer-Shelah-Perles Lemma for Sumsets）</news:title>
   <news:publication_date>2026-05-17T02:41:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691033</loc>
  <lastmod>2026-05-17T02:41:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>影響力・受容性に基づくネットワーク構造学習（Learning Influence–Receptivity Network Structure with Guarantee）</news:title>
   <news:publication_date>2026-05-17T02:41:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691031</loc>
  <lastmod>2026-05-17T02:41:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群に基づく3D臓器セグメンテーションの行動学習（Action Learning for 3D Point Cloud Based Organ Segmentation）</news:title>
   <news:publication_date>2026-05-17T02:41:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691029</loc>
  <lastmod>2026-05-17T02:40:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チタン酸塩超格子の界面電荷移動の可視化（Resolving interfacial charge transfer in titanate superlattices using resonant X-ray reflectometry）</news:title>
   <news:publication_date>2026-05-17T02:40:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691027</loc>
  <lastmod>2026-05-17T02:40:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一軌跡からの非漸近的線形系同定（Non-asymptotic Identification of LTI Systems from a Single Trajectory）</news:title>
   <news:publication_date>2026-05-17T02:40:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691025</loc>
  <lastmod>2026-05-17T01:49:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的に学ぶニューラルネットワークの新潮流（Multilevel Artificial Neural Network Training for Spatially Correlated Learning）</news:title>
   <news:publication_date>2026-05-17T01:49:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691023</loc>
  <lastmod>2026-05-17T01:49:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散型の最適潮流を学習で実現する（Towards Distributed Energy Services: Decentralizing Optimal Power Flow with Machine Learning）</news:title>
   <news:publication_date>2026-05-17T01:49:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691021</loc>
  <lastmod>2026-05-17T01:48:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WeChatにおける都市文化交流の潜在パターン発見（Discovering Latent Patterns of Urban Cultural Interactions in WeChat for Modern City Planning）</news:title>
   <news:publication_date>2026-05-17T01:48:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691019</loc>
  <lastmod>2026-05-17T01:48:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GLoMoによる伝達可能な関係グラフの学習（GLoMo: Unsupervisedly Learned Relational Graphs as Transferable Representations）</news:title>
   <news:publication_date>2026-05-17T01:48:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691017</loc>
  <lastmod>2026-05-17T01:48:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話的画像編集による深層学習解釈の手法（Interactive Classification for Deep Learning Interpretation）</news:title>
   <news:publication_date>2026-05-17T01:48:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691015</loc>
  <lastmod>2026-05-17T01:48:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>若いクエーサーの初めての分光学的研究（First Spectroscopic Study of a Young Quasar）</news:title>
   <news:publication_date>2026-05-17T01:48:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691013</loc>
  <lastmod>2026-05-17T01:47:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の光学フロー学習（Learning Human Optical Flow）</news:title>
   <news:publication_date>2026-05-17T01:47:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691011</loc>
  <lastmod>2026-05-17T00:56:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手のジェスチャー認識を二段構えで改善するHGR-Net（HGR-Net: A Fusion Network for Hand Gesture Segmentation and Recognition）</news:title>
   <news:publication_date>2026-05-17T00:56:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691009</loc>
  <lastmod>2026-05-17T00:56:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトル立方体における構造の無教師学習（Unsupervised Learning of Structure in Spectroscopic Cubes）</news:title>
   <news:publication_date>2026-05-17T00:56:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691007</loc>
  <lastmod>2026-05-17T00:56:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造を取り込むコピー機構による抽象的要約の改善（Structure-Infused Copy Mechanisms for Abstractive Summarization）</news:title>
   <news:publication_date>2026-05-17T00:56:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691005</loc>
  <lastmod>2026-05-17T00:55:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己模倣学習（Self-Imitation Learning）</news:title>
   <news:publication_date>2026-05-17T00:55:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691003</loc>
  <lastmod>2026-05-17T00:55:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測環境での学習と探索：Monte Carlo Tree Searchを用いたPOMDP学習（Learning in POMDPs with Monte Carlo Tree Search）</news:title>
   <news:publication_date>2026-05-17T00:55:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691001</loc>
  <lastmod>2026-05-17T00:54:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的補間でSAGAを改良する手法（Improving SAGA via a Probabilistic Interpolation with Gradient Descent）</news:title>
   <news:publication_date>2026-05-17T00:54:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690999</loc>
  <lastmod>2026-05-17T00:54:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模音声・音声可視化データが変えた話——VoxCeleb2による話者認識の前提転換（VoxCeleb2: Deep Speaker Recognition）</news:title>
   <news:publication_date>2026-05-17T00:54:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690997</loc>
  <lastmod>2026-05-17T00:03:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的分散低減ポリシー勾配（Stochastic Variance-Reduced Policy Gradient）</news:title>
   <news:publication_date>2026-05-17T00:03:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690995</loc>
  <lastmod>2026-05-17T00:03:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的環境下での視覚SLAMの進化（DynaSLAM: Tracking, Mapping and Inpainting in Dynamic Scenes）</news:title>
   <news:publication_date>2026-05-17T00:03:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690993</loc>
  <lastmod>2026-05-17T00:02:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ALMAディープフィールド調査と高赤方偏移（High-z）塵性銀河の不足感（An Analysis of ALMA Deep Fields and the Perceived Dearth of High-z Galaxies）</news:title>
   <news:publication_date>2026-05-17T00:02:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690991</loc>
  <lastmod>2026-05-17T00:00:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未ラベルデータを「平均化」して使う合理性（There are Many Consistent Explanations of Unlabeled Data: Why You Should Average）</news:title>
   <news:publication_date>2026-05-17T00:00:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690989</loc>
  <lastmod>2026-05-17T00:00:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>英語・ヒンディー語コードミックスの性別予測（Gender Prediction in English-Hindi Code-Mixed Social Media Content : Corpus and Baseline System）</news:title>
   <news:publication_date>2026-05-17T00:00:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690987</loc>
  <lastmod>2026-05-17T00:00:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルと認知アーキテクチャを結ぶ意味画像検索（Semantic Image Retrieval by Uniting Deep Neural Networks and Cognitive Architectures）</news:title>
   <news:publication_date>2026-05-17T00:00:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690985</loc>
  <lastmod>2026-05-16T23:59:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Tract Orientation Mapping による束特異的トラクトグラフィーの革新（Tract orientation mapping for bundle-specific tractography）</news:title>
   <news:publication_date>2026-05-16T23:59:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690983</loc>
  <lastmod>2026-05-16T23:08:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布的強化学習のための暗黙的分位ネットワーク（Implicit Quantile Networks for Distributional Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-16T23:08:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690981</loc>
  <lastmod>2026-05-16T23:08:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己回帰量子ネットワークによる生成モデル（Autoregressive Quantile Networks for Generative Modeling）</news:title>
   <news:publication_date>2026-05-16T23:08:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690979</loc>
  <lastmod>2026-05-16T23:07:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱教師あり学習による腹腔鏡動画の器具位置推定（Weakly-Supervised Learning for Tool Localization in Laparoscopic Videos）</news:title>
   <news:publication_date>2026-05-16T23:07:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690977</loc>
  <lastmod>2026-05-16T23:07:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小売店パフォーマンスのベンチマーキングと最適化のためのデータ駆動分析（Data-Driven Analytics for Benchmarking and Optimizing Retail Store Performance）</news:title>
   <news:publication_date>2026-05-16T23:07:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690975</loc>
  <lastmod>2026-05-16T23:07:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EL-GANによる車線検出の構造的改善（EL-GAN: Embedding Loss Driven Generative Adversarial Networks for Lane Detection）</news:title>
   <news:publication_date>2026-05-16T23:07:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690973</loc>
  <lastmod>2026-05-16T23:07:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心筋運動スコアリングの非局所モデリング（Cardiac Motion Scoring with Segment- and Subject-level Non-Local Modeling）</news:title>
   <news:publication_date>2026-05-16T23:07:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690971</loc>
  <lastmod>2026-05-16T23:06:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CARNによる脊椎の定量計測の自動化（Direct Automated Quantitative Measurement of Spine via Cascade Amplifier Regression Network）</news:title>
   <news:publication_date>2026-05-16T23:06:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690969</loc>
  <lastmod>2026-05-16T22:15:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>距離法とカーネル法の同値性が示すもの（The Exact Equivalence of Distance and Kernel Methods in Hypothesis Testing）</news:title>
   <news:publication_date>2026-05-16T22:15:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690967</loc>
  <lastmod>2026-05-16T22:15:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルメディアにおける改良型密度ベース空間・テキストクラスタリング（Improved Density‑Based Spatio–Textual Clustering on Social Media）</news:title>
   <news:publication_date>2026-05-16T22:15:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690965</loc>
  <lastmod>2026-05-16T22:14:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NetScore：オンデバイス運用に向けたニューラルネットワーク評価の普遍的指標（NetScore: Towards Universal Metrics for Large-scale Performance Analysis of Deep Neural Networks for Practical On-Device Edge Usage）</news:title>
   <news:publication_date>2026-05-16T22:14:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690963</loc>
  <lastmod>2026-05-16T22:13:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最大事後確率方策最適化（Maximum a Posteriori Policy Optimisation）</news:title>
   <news:publication_date>2026-05-16T22:13:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690961</loc>
  <lastmod>2026-05-16T22:13:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Sparseなサンプリングからの高密度ライトフィールド再構成（Dense Light Field Reconstruction From Sparse Sampling Using Residual Network）</news:title>
   <news:publication_date>2026-05-16T22:13:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690959</loc>
  <lastmod>2026-05-16T22:13:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>直感物理の可視化とバイアス除去（Scrutinizing and De‑Biasing Intuitive Physics with Neural Stethoscopes）</news:title>
   <news:publication_date>2026-05-16T22:13:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690957</loc>
  <lastmod>2026-05-16T22:13:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReConvNetによる動画物体領域分割の自己適応手法（ReConvNet: Video Object Segmentation with Spatio-Temporal Features Modulation）</news:title>
   <news:publication_date>2026-05-16T22:13:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690955</loc>
  <lastmod>2026-05-16T21:21:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>KASCADEデータ公開基盤が示す「オープンサイエンス」の実務化（The KASCADE Cosmic-ray Data Centre (KCDC))</news:title>
   <news:publication_date>2026-05-16T21:21:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690953</loc>
  <lastmod>2026-05-16T21:20:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リターンベースのDeep Q-Networkにおける政策差異の定性的測定（Qualitative Measurements of Policy Discrepancy for Return-Based Deep Q-Network）</news:title>
   <news:publication_date>2026-05-16T21:20:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690951</loc>
  <lastmod>2026-05-16T21:20:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ガウス過程に対するサンプリングベース推論の実践（Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo）</news:title>
   <news:publication_date>2026-05-16T21:20:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690949</loc>
  <lastmod>2026-05-16T21:19:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習とアルゴリズムゲーム理論による多数派攻撃対策（Securing Majority-Attack In Blockchain Using Machine Learning And Algorithmic Game Theory: A Proof of Work）</news:title>
   <news:publication_date>2026-05-16T21:19:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690947</loc>
  <lastmod>2026-05-16T21:19:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コピーキャットCNN：ランダム非ラベルデータで知識を盗む手法（Copycat CNN: Stealing Knowledge by Persuading Confession with Random Non-Labeled Data）</news:title>
   <news:publication_date>2026-05-16T21:19:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690945</loc>
  <lastmod>2026-05-16T21:18:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ほぼゼロショット学習による音声対話の意味解釈（Nearly Zero-Shot Learning for Semantic Decoding in Spoken Dialogue Systems）</news:title>
   <news:publication_date>2026-05-16T21:18:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690943</loc>
  <lastmod>2026-05-16T21:18:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な医用画像の能動学習と合成生成を組み合わせたサンプル選択法（Efficient Active Learning for Image Classification and Segmentation）</news:title>
   <news:publication_date>2026-05-16T21:18:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690941</loc>
  <lastmod>2026-05-16T20:27:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスリンガル論理表現の分散学習が意味解析を変える（Learning Cross-lingual Distributed Logical Representations for Semantic Parsing）</news:title>
   <news:publication_date>2026-05-16T20:27:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690939</loc>
  <lastmod>2026-05-16T20:27:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランク幾何平均距離学習（Low-rank geometric mean metric learning）</news:title>
   <news:publication_date>2026-05-16T20:27:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690937</loc>
  <lastmod>2026-05-16T20:26:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実世界医用画像における深層生成モデルの課題（Deep Generative Models in the Real-World: An Open Challenge from Medical Imaging）</news:title>
   <news:publication_date>2026-05-16T20:26:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690935</loc>
  <lastmod>2026-05-16T20:26:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ServeNet: Webサービス分類のための深層ニューラルネットワーク（ServeNet: A Deep Neural Network for Web Services Classification）</news:title>
   <news:publication_date>2026-05-16T20:26:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690933</loc>
  <lastmod>2026-05-16T20:26:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>委員会マシンにおける計算と統計のギャップ（The committee machine: Computational to statistical gaps in learning a two-layers neural network）</news:title>
   <news:publication_date>2026-05-16T20:26:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690931</loc>
  <lastmod>2026-05-16T20:26:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>期待される分類誤差の指数収束を示した確率的勾配降下法（Stochastic Gradient Descent with Exponential Convergence Rates of Expected Classification Errors）</news:title>
   <news:publication_date>2026-05-16T20:26:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690929</loc>
  <lastmod>2026-05-16T20:25:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチターン情報探索会話における文脈対応質問マッチングのための転移学習（Transfer Learning for Context-Aware Question Matching in Information-seeking Conversations in E-commerce）</news:title>
   <news:publication_date>2026-05-16T20:25:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690927</loc>
  <lastmod>2026-05-16T19:34:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウルドゥー語の単語分割における条件付き確率場（CRF）を用いた手法（Urdu Word Segmentation using Conditional Random Fields (CRFs))</news:title>
   <news:publication_date>2026-05-16T19:34:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690925</loc>
  <lastmod>2026-05-16T19:34:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピアツーピアネットワークにおけるプライバシー保護付きデータ符号化（An Effective Privacy-Preserving Data Coding in Peer-To-Peer Network）</news:title>
   <news:publication_date>2026-05-16T19:34:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690923</loc>
  <lastmod>2026-05-16T19:33:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパースペース探索が変える設計判断（Hyper Space Exploration: A Multicriterial Quantitative Trade-Off Analysis for System Design in Complex Environment）</news:title>
   <news:publication_date>2026-05-16T19:33:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690921</loc>
  <lastmod>2026-05-16T19:33:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セルフレスな逐次学習（Selfless Sequential Learning）</news:title>
   <news:publication_date>2026-05-16T19:33:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690919</loc>
  <lastmod>2026-05-16T19:33:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>環境を“調整”できる学習問題の設計と解法（Conﬁgurable Markov Decision Processes）</news:title>
   <news:publication_date>2026-05-16T19:33:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690917</loc>
  <lastmod>2026-05-16T19:33:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RTL NNアクセラレータの耐故障性（On the Resilience of RTL NN Accelerators）</news:title>
   <news:publication_date>2026-05-16T19:33:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690915</loc>
  <lastmod>2026-05-16T19:32:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限定的な比較からのランキング回復（Ranking Recovery from Limited Comparisons using Low-Rank Matrix Completion）</news:title>
   <news:publication_date>2026-05-16T19:32:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690913</loc>
  <lastmod>2026-05-16T18:42:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形デノイジングオートエンコーダの学習ダイナミクス（Learning Dynamics of Linear Denoising Autoencoders）</news:title>
   <news:publication_date>2026-05-16T18:42:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690911</loc>
  <lastmod>2026-05-16T18:42:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーセプトロンの圧縮について（On the Perceptron’s Compression）</news:title>
   <news:publication_date>2026-05-16T18:42:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690909</loc>
  <lastmod>2026-05-16T18:41:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲーティングがRNNの信号伝搬を可能にする仕組み（Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-05-16T18:41:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690907</loc>
  <lastmod>2026-05-16T18:41:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粒子フィルタによるパラメータ学習と変化検出（Parameter Learning and Change Detection Using a Particle Filter With Accelerated Adaptation）</news:title>
   <news:publication_date>2026-05-16T18:41:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690905</loc>
  <lastmod>2026-05-16T18:41:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的等方性とCNNの平均場理論（Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-16T18:41:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690903</loc>
  <lastmod>2026-05-16T18:41:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意統計に基づくチャネル剪定（PCAS: Pruning Channels with Attention Statistics）</news:title>
   <news:publication_date>2026-05-16T18:41:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690901</loc>
  <lastmod>2026-05-16T18:41:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大学レベルの学生向けEラーニングの現状と評価（A TOUR OF THE STUDENT’S E-LEARNING PUDDLE）</news:title>
   <news:publication_date>2026-05-16T18:41:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690899</loc>
  <lastmod>2026-05-16T17:50:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多重注意と多クラス制約による微細画像認識の改良（Multi-Attention Multi-Class Constraint for Fine-grained Image Recognition）</news:title>
   <news:publication_date>2026-05-16T17:50:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690897</loc>
  <lastmod>2026-05-16T17:49:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一深度画像からの意味的シーン補完のためのView-Volumeネットワーク (View-Volume Network for Semantic Scene Completion from a Single Depth Image)</news:title>
   <news:publication_date>2026-05-16T17:49:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690895</loc>
  <lastmod>2026-05-16T17:49:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報検索ゲームにおける学習ダイナミクスの収束（Convergence of Learning Dynamics in Information Retrieval Games）</news:title>
   <news:publication_date>2026-05-16T17:49:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690893</loc>
  <lastmod>2026-05-16T17:49:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サドルポイント攻撃から分散学習を守る方法（Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning）</news:title>
   <news:publication_date>2026-05-16T17:49:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690891</loc>
  <lastmod>2026-05-16T17:48:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GEMSによる高次元グラフ信号の多重尺度辞書学習（Finding GEMS: Multi-Scale Dictionaries for High-Dimensional Graph Signals）</news:title>
   <news:publication_date>2026-05-16T17:48:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690889</loc>
  <lastmod>2026-05-16T17:48:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークの圧縮と剪定（Scalable Neural Network Compression and Pruning Using Hard Clustering and L1 Regularization）</news:title>
   <news:publication_date>2026-05-16T17:48:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690887</loc>
  <lastmod>2026-05-16T17:48:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層多出力予測による血糖値軌跡の精密予測 (Deep Multi-Output Forecasting: Learning to Accurately Predict Blood Glucose Trajectories)</news:title>
   <news:publication_date>2026-05-16T17:48:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690885</loc>
  <lastmod>2026-05-16T16:57:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予告編から物語を学ぶ効率的手法（From Trailers to Storylines: An Efficient Way to Learn from Movies）</news:title>
   <news:publication_date>2026-05-16T16:57:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690883</loc>
  <lastmod>2026-05-16T16:57:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成可能性をネットワークで読む──計算材料探索の新しい地図（Network analysis of synthesizable materials discovery）</news:title>
   <news:publication_date>2026-05-16T16:57:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690881</loc>
  <lastmod>2026-05-16T16:56:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワーク予測の階層的解釈（HIERARCHICAL INTERPRETATIONS FOR NEURAL NETWORK PREDICTIONS）</news:title>
   <news:publication_date>2026-05-16T16:56:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690879</loc>
  <lastmod>2026-05-16T16:56:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非極性m面 GaN-on-GaN 縦型 p-n パワーダイオードの実証（Demonstration of nonpolar m-plane vertical GaN-on-GaN p-n power diodes grown on free-standing GaN substrates）</news:title>
   <news:publication_date>2026-05-16T16:56:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690877</loc>
  <lastmod>2026-05-16T16:55:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人工ニューラルネットワーク入門（Apuntes de Redes Neuronales Artificiales）</news:title>
   <news:publication_date>2026-05-16T16:55:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690875</loc>
  <lastmod>2026-05-16T16:55:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市交通における深層強化学習の応用（Deep Reinforcement Learning for Dynamic Urban Transportation Problems）</news:title>
   <news:publication_date>2026-05-16T16:55:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690873</loc>
  <lastmod>2026-05-16T16:55:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトルクラスタリングを用いたフィルタ剪定と自己適応的ソフト手法（SCSP: Spectral Clustering Filter Pruning with Soft Self-adaption Manners）</news:title>
   <news:publication_date>2026-05-16T16:55:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690871</loc>
  <lastmod>2026-05-16T16:04:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速で柔軟な畳み込みソルバーと写真写実的スタイル転送（A Flexible Convolutional Solver with Application to Photorealistic Style Transfer）</news:title>
   <news:publication_date>2026-05-16T16:04:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690869</loc>
  <lastmod>2026-05-16T16:04:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>抽象機械の自動生成による階層強化学習の構造化（Automatic formation of the structure of abstract machines in hierarchical reinforcement learning with state clustering）</news:title>
   <news:publication_date>2026-05-16T16:04:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690867</loc>
  <lastmod>2026-05-16T16:03:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パターン依存性検出のためのn-TARPクラスタリング（Pattern Dependence Detection using n-TARP Clustering）</news:title>
   <news:publication_date>2026-05-16T16:03:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690865</loc>
  <lastmod>2026-05-16T16:02:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホースシュー事前分布を用いたベイズニューラルネットワークの構造化変分学習（Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors）</news:title>
   <news:publication_date>2026-05-16T16:02:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690863</loc>
  <lastmod>2026-05-16T16:02:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元パターン認識問題のベンチマーク提案（Benchmarks for Image Classification and Other High-dimensional Pattern Recognition Problems）</news:title>
   <news:publication_date>2026-05-16T16:02:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690861</loc>
  <lastmod>2026-05-16T16:02:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>応用されるフェアネスの実務的重要性（What About Applied Fairness?）</news:title>
   <news:publication_date>2026-05-16T16:02:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690859</loc>
  <lastmod>2026-05-16T16:02:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長距離自己教師ありシーン分割によるMAVのオンライン適応（Online Self-supervised Scene Segmentation for Micro Aerial Vehicles）</news:title>
   <news:publication_date>2026-05-16T16:02:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690857</loc>
  <lastmod>2026-05-16T15:10:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Manifold Mixupによる内部表現の改善（Manifold Mixup: Better Representations by Interpolating Hidden States）</news:title>
   <news:publication_date>2026-05-16T15:10:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690855</loc>
  <lastmod>2026-05-16T15:10:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳MRIを用いたパーキンソン病のエンドツーエンド診断（End-to-End Parkinson Disease Diagnosis using Brain MR-Images by 3D-CNN）</news:title>
   <news:publication_date>2026-05-16T15:10:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690853</loc>
  <lastmod>2026-05-16T15:10:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Boosted Trainingによる大規模3Dセグメンテーションの高速化と品質向上（Boosted Training of Convolutional Neural Networks for Multi-Class Segmentation）</news:title>
   <news:publication_date>2026-05-16T15:10:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690851</loc>
  <lastmod>2026-05-16T15:08:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再現性と一般化性を同時に問う：ターゲット依存センチメント分析の再現研究（Bringing replication and reproduction together with generalisability in NLP: Three reproduction studies for Target Dependent Sentiment Analysis）</news:title>
   <news:publication_date>2026-05-16T15:08:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690849</loc>
  <lastmod>2026-05-16T15:08:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D-CODEDによる3D対応付け（3D Correspondences by Deep Deformation）</news:title>
   <news:publication_date>2026-05-16T15:08:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690847</loc>
  <lastmod>2026-05-16T15:08:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Impostor Networksによる高速な精緻分類の実現（Impostor Networks for Fast Fine-Grained Recognition）</news:title>
   <news:publication_date>2026-05-16T15:08:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690845</loc>
  <lastmod>2026-05-16T15:08:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然画像のノイズ除去における繰り返しパターン検出と深層学習（Identifying Recurring Patterns with Deep Neural Networks for Natural Image Denoising）</news:title>
   <news:publication_date>2026-05-16T15:08:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690843</loc>
  <lastmod>2026-05-16T14:16:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合したサブミリ波銀河におけるCO調査：伴侶、トリガー、環境（An ALMA survey of CO in submillimetre galaxies: companions, triggering, and the environment in blended sources）</news:title>
   <news:publication_date>2026-05-16T14:16:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690841</loc>
  <lastmod>2026-05-16T14:16:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンド機械学習の再現性を可能にする（Enabling End-To-End Machine Learning Replicability: A Case Study in Educational Data Mining）</news:title>
   <news:publication_date>2026-05-16T14:16:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690839</loc>
  <lastmod>2026-05-16T14:15:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>KYDISC: 銀河クラスタにおける形態、消光（クエンチング）、合併の深堀り（KYDISC: Galaxy Morphology, Quenching, and Mergers in the Cluster Environment）</news:title>
   <news:publication_date>2026-05-16T14:15:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690837</loc>
  <lastmod>2026-05-16T14:14:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークのより厳密な一般化境界（On Tighter Generalization Bounds for Deep Neural Networks: CNNs, ResNets, and Beyond）</news:title>
   <news:publication_date>2026-05-16T14:14:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690835</loc>
  <lastmod>2026-05-16T14:14:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経食道心エコーの自動評価が変える研修の現場（Automated Performance Assessment in Transoesophageal Echocardiography with Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-16T14:14:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690833</loc>
  <lastmod>2026-05-16T14:14:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>過学習か完全適合か？　補間する分類・回帰ルールのリスク境界（Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate）</news:title>
   <news:publication_date>2026-05-16T14:14:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690831</loc>
  <lastmod>2026-05-16T14:13:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地図を活用して学習するUAV通信（Learning to Communicate in UAV-aided Wireless Networks: Map-based Approaches）</news:title>
   <news:publication_date>2026-05-16T14:13:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690829</loc>
  <lastmod>2026-05-16T13:22:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスモーダル・ハルシネーションによる少数ショットの微細識別（Cross-modal Hallucination for Few-shot Fine-grained Recognition）</news:title>
   <news:publication_date>2026-05-16T13:22:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690827</loc>
  <lastmod>2026-05-16T13:22:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラグランジアン関数のランドスケープと制約付き非凸最適化の確率的探索（On Landscape of Lagrangian Function and Stochastic Search for Constrained Nonconvex Optimization）</news:title>
   <news:publication_date>2026-05-16T13:22:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690825</loc>
  <lastmod>2026-05-16T13:22:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューロモルフィック計算における混合信号ニューロンの極限的省エネ化（Exploiting Inherent Error-Resiliency of Neuromorphic Computing to achieve Extreme Energy-Efficiency through Mixed-Signal Neurons）</news:title>
   <news:publication_date>2026-05-16T13:22:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690823</loc>
  <lastmod>2026-05-16T13:21:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味を捉える翻訳モデルの新潮流：Generative Neural Machine Translation（Generative Neural Machine Translation）</news:title>
   <news:publication_date>2026-05-16T13:21:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690821</loc>
  <lastmod>2026-05-16T13:20:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>開発者Q/A会話におけるスピーチアクト検出（Detecting Speech Act Types in Developer Question/Answer Conversations During Bug Repair）</news:title>
   <news:publication_date>2026-05-16T13:20:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690819</loc>
  <lastmod>2026-05-16T13:20:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有界行動空間に対するマージナル方策勾配の統一的枠組み（Marginal Policy Gradients: A Unified Family of Estimators for Bounded Action Spaces with Applications）</news:title>
   <news:publication_date>2026-05-16T13:20:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690817</loc>
  <lastmod>2026-05-16T13:20:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタベースのグラフィカルモデルに関する高次元推論（High-Dimensional Inference for Cluster-Based Graphical Models）</news:title>
   <news:publication_date>2026-05-16T13:20:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690814</loc>
  <lastmod>2026-05-16T12:29:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バックトラッキング付きフランク–ウォルフ法の線形収束（Linearly Convergent Frank-Wolfe with Backtracking Line-Search）</news:title>
   <news:publication_date>2026-05-16T12:29:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690812</loc>
  <lastmod>2026-05-16T12:19:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>上空画像から地上の密な視点を生成する（What Is It Like Down There? Generating Dense Ground-Level Views and Image Features From Overhead Imagery Using Conditional Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-16T12:19:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690810</loc>
  <lastmod>2026-05-16T12:19:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FPSゲームにおける射撃学習の強化学習手法（Learning to Shoot in First Person Shooter Games by Stabilizing Actions and Clustering Rewards for Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-16T12:19:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690808</loc>
  <lastmod>2026-05-16T12:18:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己教師ありシアミーズネットワークによる脳領域分割の改善（Improving Cytoarchitectonic Segmentation of Human Brain Areas with Self-supervised Siamese Networks）</news:title>
   <news:publication_date>2026-05-16T12:18:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690806</loc>
  <lastmod>2026-05-16T12:17:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層化Sarsa(λ)で学ぶゲームAIの設計思想（DRE-Bot: A Hierarchical First Person Shooter Bot Using Multiple Sarsa(λ) Reinforcement Learners）</news:title>
   <news:publication_date>2026-05-16T12:17:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690804</loc>
  <lastmod>2026-05-16T12:17:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>社会的成果に基づく公平性基準の比較 (Comparing Fairness Criteria Based on Social Outcome)</news:title>
   <news:publication_date>2026-05-16T12:17:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690802</loc>
  <lastmod>2026-05-16T12:17:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザー指定制約を導入したマルコフ連鎖による非線形次元削減（Introducing user-prescribed constraints in Markov chains for nonlinear dimensionality reduction）</news:title>
   <news:publication_date>2026-05-16T12:17:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690800</loc>
  <lastmod>2026-05-16T11:26:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>評価スコアの誤較正を越える判断法（Your 2 is My 1, Your 3 is My 9: Handling Arbitrary Miscalibrations in Ratings）</news:title>
   <news:publication_date>2026-05-16T11:26:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690798</loc>
  <lastmod>2026-05-16T11:25:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群等変カプセルネットワーク（Group Equivariant Capsule Networks）</news:title>
   <news:publication_date>2026-05-16T11:25:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690796</loc>
  <lastmod>2026-05-16T11:25:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒストパソロジー画像に対する複数インスタンス学習（Multiple Instance Learning for Heterogeneous Images: Training a CNN for Histopathology）</news:title>
   <news:publication_date>2026-05-16T11:25:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690794</loc>
  <lastmod>2026-05-16T11:24:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>双方向再帰ニューラルネットワークによる平行文抽出（Extracting Parallel Sentences with Bidirectional Recurrent Neural Networks to Improve Machine Translation）</news:title>
   <news:publication_date>2026-05-16T11:24:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690792</loc>
  <lastmod>2026-05-16T11:24:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MAP推論を速く安定にする手法の本質（MAP inference via Block-Coordinate Frank-Wolfe Algorithm）</news:title>
   <news:publication_date>2026-05-16T11:24:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690790</loc>
  <lastmod>2026-05-16T11:24:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定ランクに基づく一般化持続性解析（GENERALIZED PERSISTENCE ANALYSIS BASED ON STABLE RANK INVARIANT）</news:title>
   <news:publication_date>2026-05-16T11:24:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690788</loc>
  <lastmod>2026-05-16T11:24:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バンディット型オンライン最適化における後悔の最小化（Minimizing Regret of Bandit Online Optimization in Unconstrained Action Spaces）</news:title>
   <news:publication_date>2026-05-16T11:24:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690786</loc>
  <lastmod>2026-05-16T10:33:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>あいまい画像のための確率的U-Net（A Probabilistic U-Net for Segmentation of Ambiguous Images）</news:title>
   <news:publication_date>2026-05-16T10:33:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690784</loc>
  <lastmod>2026-05-16T10:32:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人工物を見抜くことで学ぶ自己教師あり特徴学習（Self-Supervised Feature Learning by Learning to Spot Artifacts）</news:title>
   <news:publication_date>2026-05-16T10:32:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690782</loc>
  <lastmod>2026-05-16T10:32:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補助情報を統合した深層系列学習による交通予測（Deep Sequence Learning with Auxiliary Information for Traffic Prediction）</news:title>
   <news:publication_date>2026-05-16T10:32:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690780</loc>
  <lastmod>2026-05-16T10:32:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イオン液体における回転運動が電荷輸送を決める（Importance of reorientational dynamics for the charge transport in ionic liquids）</news:title>
   <news:publication_date>2026-05-16T10:32:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690778</loc>
  <lastmod>2026-05-16T10:32:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠損EEGデータに対するテンソル補完によるBCI改善（Brain-Computer Interface with Corrupted EEG Data: A Tensor Completion Approach）</news:title>
   <news:publication_date>2026-05-16T10:32:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690776</loc>
  <lastmod>2026-05-16T10:31:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>主観的ラベルを持つタスクのためのシミュレーションによる説明可能な合意（Explainable Agreement through Simulation for Tasks with Subjective Labels）</news:title>
   <news:publication_date>2026-05-16T10:31:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690774</loc>
  <lastmod>2026-05-16T10:31:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木構造の編集距離学習と適応的記号埋め込み（Tree Edit Distance Learning via Adaptive Symbol Embeddings）</news:title>
   <news:publication_date>2026-05-16T10:31:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690772</loc>
  <lastmod>2026-05-16T09:40:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストリーミング・ロールアウトによる完全モデル並列化（The streaming rollout of deep networks - towards fully model-parallel execution）</news:title>
   <news:publication_date>2026-05-16T09:40:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690770</loc>
  <lastmod>2026-05-16T09:31:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的キャンバスによる文章生成（Generating Sentences Using a Dynamic Canvas）</news:title>
   <news:publication_date>2026-05-16T09:31:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690768</loc>
  <lastmod>2026-05-16T09:31:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳MRIにおける病変の教師なし検出（Unsupervised Detection of Lesions in Brain MRI using constrained adversarial auto-encoders）</news:title>
   <news:publication_date>2026-05-16T09:31:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690766</loc>
  <lastmod>2026-05-16T09:31:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズだけがマニフォールドを学ぶべきである（Only Bayes should learn a manifold）</news:title>
   <news:publication_date>2026-05-16T09:31:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690764</loc>
  <lastmod>2026-05-16T09:30:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味的に強化されたデータ理解への接近（Towards Semantically Enhanced Data Understanding）</news:title>
   <news:publication_date>2026-05-16T09:30:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690762</loc>
  <lastmod>2026-05-16T09:30:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>fMRIによる意味カテゴリ復号と単語埋め込みによる言語的表現の応用（fMRI Semantic Category Decoding using Linguistic Encoding of Word Embeddings）</news:title>
   <news:publication_date>2026-05-16T09:30:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690760</loc>
  <lastmod>2026-05-16T09:30:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウド駆動データマイニングの全体像（Crowd-Powered Data Mining）</news:title>
   <news:publication_date>2026-05-16T09:30:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690758</loc>
  <lastmod>2026-05-16T08:38:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Far-HOによるハイパーパラメータ最適化とメタラーニングの統一的アプローチ（Far-HO: A Bilevel Programming Package for Hyperparameter Optimization and Meta-Learning）</news:title>
   <news:publication_date>2026-05-16T08:38:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690756</loc>
  <lastmod>2026-05-16T08:28:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DNA配列を画像化してCNNで読む新手法（An image representation based convolutional network for DNA classification）</news:title>
   <news:publication_date>2026-05-16T08:28:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690754</loc>
  <lastmod>2026-05-16T08:28:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>πrセレマー共伴モジュラー形式（pr-SELMER COMPANION MODULAR FORMS）</news:title>
   <news:publication_date>2026-05-16T08:28:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690752</loc>
  <lastmod>2026-05-16T08:27:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報エントロピーで最適化するアンサンブル剪定（Ensemble Pruning based on Objection Maximization with a General Distributed Framework）</news:title>
   <news:publication_date>2026-05-16T08:27:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690750</loc>
  <lastmod>2026-05-16T08:27:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中間レベルの音楽知覚特徴をデータ駆動でモデル化する（A Data-Driven Approach to Mid-Level Perceptual Musical Feature Modeling）</news:title>
   <news:publication_date>2026-05-16T08:27:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690748</loc>
  <lastmod>2026-05-16T08:27:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビデオゲーム向けアイテム推薦の機械学習システム（A Machine-Learning Item Recommendation System for Video Games）</news:title>
   <news:publication_date>2026-05-16T08:27:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690746</loc>
  <lastmod>2026-05-16T08:27:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーパラメータ最適化とメタラーニングの二重最適化枠組み（Bilevel Programming for Hyperparameter Optimization and Meta-Learning）</news:title>
   <news:publication_date>2026-05-16T08:27:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690744</loc>
  <lastmod>2026-05-16T07:35:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マトリクス補完による単一個体ハプロタイプ推定の性能保証（Matrix Completion and Performance Guarantees for Single Individual Haplotyping）</news:title>
   <news:publication_date>2026-05-16T07:35:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690742</loc>
  <lastmod>2026-05-16T07:35:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ReLUニューラルネットワークの局所解に関するNTK領域での解析（Spurious Local Minima of Deep ReLU Neural Networks in the Neural Tangent Kernel Regime）</news:title>
   <news:publication_date>2026-05-16T07:35:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690740</loc>
  <lastmod>2026-05-16T07:34:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な因子分離表現による教師なし適応（Unsupervised Adaptation with Interpretable Disentangled Representations for Distant Conversational Speech Recognition）</news:title>
   <news:publication_date>2026-05-16T07:34:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690738</loc>
  <lastmod>2026-05-16T07:34:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所座標符号化を用いた敵対的学習（Adversarial Learning with Local Coordinate Coding）</news:title>
   <news:publication_date>2026-05-16T07:34:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690736</loc>
  <lastmod>2026-05-16T07:34:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cell Identity Codesによる細胞同定の再考（Cell Identity Codes: Understanding Cell Identity from Gene Expression Profiles using Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-16T07:34:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690734</loc>
  <lastmod>2026-05-16T07:33:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚知識メモリネットワークによるVQAへの応用（Learning Visual Knowledge Memory Networks for Visual Question Answering）</news:title>
   <news:publication_date>2026-05-16T07:33:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690732</loc>
  <lastmod>2026-05-16T07:33:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>織り目運動（weaving）標的の周波数推定における深層学習の有用性（Deep Learning based Estimation of Weaving Target Maneuvers）</news:title>
   <news:publication_date>2026-05-16T07:33:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690730</loc>
  <lastmod>2026-05-16T06:42:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーケンス対シーケンス学習を変える二重経路設計（Double Path Networks for Sequence to Sequence Learning）</news:title>
   <news:publication_date>2026-05-16T06:42:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690728</loc>
  <lastmod>2026-05-16T06:42:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ深層学習の高速化と拡張性（Bayesian Deep Learning by Weight-Perturbation in Adam）</news:title>
   <news:publication_date>2026-05-16T06:42:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690726</loc>
  <lastmod>2026-05-16T06:41:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層ニューラルネットは結局多項式回帰だったのか（Polynomial Regression as an Alternative to Neural Nets）</news:title>
   <news:publication_date>2026-05-16T06:41:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690724</loc>
  <lastmod>2026-05-16T06:41:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近接音声から遠隔音声へのドメイン適応手法の比較（A Study of Enhancement, Augmentation, and Autoencoder Methods for Domain Adaptation in Distant Speech Recognition）</news:title>
   <news:publication_date>2026-05-16T06:41:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690722</loc>
  <lastmod>2026-05-16T06:41:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な分割埋め込みによるカスタマイズされたファッションコーディネート（Interpretable Partitioned Embedding for Customized Fashion Outfit Composition）</news:title>
   <news:publication_date>2026-05-16T06:41:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690720</loc>
  <lastmod>2026-05-16T06:41:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関数値アクション空間を用いた偏微分方程式制御（Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control）</news:title>
   <news:publication_date>2026-05-16T06:41:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690718</loc>
  <lastmod>2026-05-16T06:40:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分AUC（pAUC）を直接最大化する非線形スコアリング関数の提案（Partial AUC Maximization via Nonlinear Scoring Functions）</news:title>
   <news:publication_date>2026-05-16T06:40:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690716</loc>
  <lastmod>2026-05-16T05:49:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形半準パラメトリックモデルの正則化直交機械学習（Regularized Orthogonal Machine Learning for Nonlinear Semiparametric Models）</news:title>
   <news:publication_date>2026-05-16T05:49:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690714</loc>
  <lastmod>2026-05-16T05:49:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層深層学習によるマルチスケールモデル学習（Deep Multiscale Model Learning）</news:title>
   <news:publication_date>2026-05-16T05:49:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690712</loc>
  <lastmod>2026-05-16T05:49:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>閉じ込められた電磁場における光子スキルミオンの深サブ波長特性（Deep-subwavelength features of photonic skyrmions in a confined electromagnetic field with orbital angular momentum）</news:title>
   <news:publication_date>2026-05-16T05:49:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690710</loc>
  <lastmod>2026-05-16T05:48:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汎用的なスタイル転送の統一フレームワーク（A Unified Framework for Generalizable Style Transfer: Style and Content Separation）</news:title>
   <news:publication_date>2026-05-16T05:48:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690708</loc>
  <lastmod>2026-05-16T05:48:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>積分プライバシーに基づくサンプリング手法（Integral Privacy for Sampling）</news:title>
   <news:publication_date>2026-05-16T05:48:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690706</loc>
  <lastmod>2026-05-16T05:48:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EHRに基づく計算表現型のための自然言語処理の実践と示唆（Natural Language Processing for EHR-Based Computational Phenotyping）</news:title>
   <news:publication_date>2026-05-16T05:48:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690704</loc>
  <lastmod>2026-05-16T05:48:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱い教師あり学習が情報検索（IR）を変える理由（Towards Theoretical Understanding of Weak Supervision for Information Retrieval）</news:title>
   <news:publication_date>2026-05-16T05:48:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690702</loc>
  <lastmod>2026-05-16T04:56:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BA-Net: Dense Bundle Adjustment を用いた密なカメラ姿勢と深度復元（BA-NET: DENSE BUNDLE ADJUSTMENT NETWORKS）</news:title>
   <news:publication_date>2026-05-16T04:56:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690700</loc>
  <lastmod>2026-05-16T04:56:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超高次元データの表現学習で距離ベース外れ値検出を強化する（Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection）</news:title>
   <news:publication_date>2026-05-16T04:56:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690698</loc>
  <lastmod>2026-05-16T04:56:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習による転移可能な能動学習ポリシーのメタ学習 (Meta-Learning Transferable Active Learning Policies by Deep Reinforcement Learning)</news:title>
   <news:publication_date>2026-05-16T04:56:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690696</loc>
  <lastmod>2026-05-16T04:55:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低精度数値での深層学習推論を加速するFPGAの可能性（Exploration of Low Numeric Precision Deep Learning Inference Using Intel® FPGAs）</news:title>
   <news:publication_date>2026-05-16T04:55:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690694</loc>
  <lastmod>2026-05-16T04:55:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Ni-Mo合金とFCC金属の量子精度SNAPモデル（Quantum-Accurate Spectral Neighbor Analysis Potential Models for Ni-Mo Binary Alloys and FCC Metals）</news:title>
   <news:publication_date>2026-05-16T04:55:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690692</loc>
  <lastmod>2026-05-16T04:55:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連結網に基づく六角格子畳み込みモデルによるハエ視覚系の再現（A Connectome Based Hexagonal Lattice Convolutional Network Model of the Drosophila Visual System）</news:title>
   <news:publication_date>2026-05-16T04:55:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690690</loc>
  <lastmod>2026-05-16T04:54:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Drive2Vecによる車両センサーデータの多尺度状態埋め込み（Drive2Vec: Multiscale State-Space Embedding of Vehicular Sensor Data）</news:title>
   <news:publication_date>2026-05-16T04:54:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690688</loc>
  <lastmod>2026-05-16T04:03:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>静的マルウェア検出とすり替え：機械学習と従来アンチウイルスの堅牢性を定量化する（Static Malware Detection &amp;amp; Subterfuge: Quantifying the Robustness of Machine Learning and Current Anti-Virus）</news:title>
   <news:publication_date>2026-05-16T04:03:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690686</loc>
  <lastmod>2026-05-16T04:03:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイム端末内での頷き・首振り検出（REAL-TIME ON-DEVICE NOD AND SHAKE RECOGNITION）</news:title>
   <news:publication_date>2026-05-16T04:03:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690684</loc>
  <lastmod>2026-05-16T04:02:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なしで長期動画予測を実現する階層モデル（Hierarchical Long-term Video Prediction without Supervision）</news:title>
   <news:publication_date>2026-05-16T04:02:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690682</loc>
  <lastmod>2026-05-16T04:02:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有機電解質トランジスタ配列による神経形態学的時間依存パターン分類（Neuromorphic Time-Dependent Pattern Classification with Organic Electrochemical Transistor Arrays）</news:title>
   <news:publication_date>2026-05-16T04:02:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690680</loc>
  <lastmod>2026-05-16T04:02:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>INFERNO: 推論重視ニューラル最適化（INFERNO: Inference-Aware Neural Optimisation）</news:title>
   <news:publication_date>2026-05-16T04:02:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690678</loc>
  <lastmod>2026-05-16T04:01:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚メラノーマ診断のための全畳み込みネットワーク（Fully Convolutional Network for Melanoma Diagnostics）</news:title>
   <news:publication_date>2026-05-16T04:01:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690676</loc>
  <lastmod>2026-05-16T04:01:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リソース効率化されたニューラル設計（Resource-Efficient Neural Architect）</news:title>
   <news:publication_date>2026-05-16T04:01:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690674</loc>
  <lastmod>2026-05-16T03:09:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FigureNet：科学図表への問い合せに答える深層学習モデル（FigureNet: A Deep Learning model for Question-Answering on Scientific Plots）</news:title>
   <news:publication_date>2026-05-16T03:09:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690672</loc>
  <lastmod>2026-05-16T03:01:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>∆-encoderによる少数ショット分類のためのサンプル合成（∆-encoder: an effective sample synthesis method for few-shot object recognition）</news:title>
   <news:publication_date>2026-05-16T03:01:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690670</loc>
  <lastmod>2026-05-16T03:01:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RepMetによる代表ベクトルを用いた距離学習の再定義（RepMet: Representative-based metric learning for classification and few-shot object detection）</news:title>
   <news:publication_date>2026-05-16T03:01:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690668</loc>
  <lastmod>2026-05-16T03:01:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>気候モデルにおけるサブグリッド過程の深層学習による表現（Deep learning to represent sub-grid processes in climate models）</news:title>
   <news:publication_date>2026-05-16T03:01:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690666</loc>
  <lastmod>2026-05-16T03:00:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頭部CTにおける内耳の高精度検出（Accurate Detection of Inner Ears in Head CTs Using a Deep Volume-to-Volume Regression Network with False Positive Suppression and a Shape-Based Constraint）</news:title>
   <news:publication_date>2026-05-16T03:00:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690664</loc>
  <lastmod>2026-05-16T02:59:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カプセルルーティングによる音響イベント検出（Capsule Routing for Sound Event Detection）</news:title>
   <news:publication_date>2026-05-16T02:59:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690662</loc>
  <lastmod>2026-05-16T02:59:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河群3C 88におけるAGNフィードバックの実証（AGN Feedback in Galaxy Group 3C 88: Cavities, Shock and Jet Reorientation）</news:title>
   <news:publication_date>2026-05-16T02:59:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690660</loc>
  <lastmod>2026-05-16T02:08:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オートエンコーダに対する敵対的攻撃とその示唆（Adversarial Attacks on Variational Autoencoders）</news:title>
   <news:publication_date>2026-05-16T02:08:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690658</loc>
  <lastmod>2026-05-16T01:58:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フクロウ星雲と他のストリギフォーム星雲：充填殻内の多極洞（The Owl and other strigiform nebulae: multipolar cavities within a filled shell）</news:title>
   <news:publication_date>2026-05-16T01:58:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690656</loc>
  <lastmod>2026-05-16T01:58:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可換部分代数の順序構造に見る量子と古典の接点（Symmetries in exact Bohriﬁcation）</news:title>
   <news:publication_date>2026-05-16T01:58:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690654</loc>
  <lastmod>2026-05-16T01:57:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トラクトグラフィーの収束性評価法（Measures of Tractography Convergence）</news:title>
   <news:publication_date>2026-05-16T01:57:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690652</loc>
  <lastmod>2026-05-16T01:57:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なしメタ強化学習による環境特化型学習手順の自動獲得（Unsupervised Meta-Learning for Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-16T01:57:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690650</loc>
  <lastmod>2026-05-16T01:57:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴選択と辞書学習による1次元時系列の地震検出 (Earthquake Detection in 1-D Time Series Data with Feature Selection and Dictionary Learning)</news:title>
   <news:publication_date>2026-05-16T01:57:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690648</loc>
  <lastmod>2026-05-16T01:57:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予測モデルを用いた模倣学習の高速化（Accelerating Imitation Learning with Predictive Models）</news:title>
   <news:publication_date>2026-05-16T01:57:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690646</loc>
  <lastmod>2026-05-16T01:05:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イププロフェン錠剤の3D微細構造の特性化（CHARACTERIZATION OF THE 3D MICROSTRUCTURE OF IBUPROFEN TABLETS BY MEANS OF SYNCHROTRON TOMOGRAPHY）</news:title>
   <news:publication_date>2026-05-16T01:05:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690644</loc>
  <lastmod>2026-05-16T01:05:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経験の整理：連続状態領域におけるサンプルベース計画のリプレイ機構の再検討（Organizing Experience: A Deeper Look at Replay Mechanisms for Sample-based Planning in Continuous State Domains）</news:title>
   <news:publication_date>2026-05-16T01:05:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690642</loc>
  <lastmod>2026-05-16T01:05:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>冗長なメソッドコメントを検出する深層学習（Deep Learning to Detect Redundant Method Comments）</news:title>
   <news:publication_date>2026-05-16T01:05:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690640</loc>
  <lastmod>2026-05-16T01:04:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合データと欠損値に強いベイズ的因子モデル（A Novel Bayesian Approach for Latent Variable Modeling from Mixed Data with Missing Values）</news:title>
   <news:publication_date>2026-05-16T01:04:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690638</loc>
  <lastmod>2026-05-16T01:04:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストリーミングPCAと部分空間トラッキング（Streaming PCA and Subspace Tracking: The Missing Data Case）</news:title>
   <news:publication_date>2026-05-16T01:04:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690636</loc>
  <lastmod>2026-05-16T01:04:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布的損失による回帰性能の改善（Improving Regression Performance with Distributional Losses）</news:title>
   <news:publication_date>2026-05-16T01:04:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690634</loc>
  <lastmod>2026-05-16T01:04:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンザフライネイティブアンサンブルによる知識蒸留（Knowledge Distillation by On-the-Fly Native Ensemble）</news:title>
   <news:publication_date>2026-05-16T01:04:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690632</loc>
  <lastmod>2026-05-16T00:13:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーキューブ上の指数重み法を多項式時間で実行する（Exponential Weights on the Hypercube in Polynomial Time）</news:title>
   <news:publication_date>2026-05-16T00:13:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690630</loc>
  <lastmod>2026-05-16T00:13:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Inherent Structureに基づくLean 2層RBMの設計（Using Inherent Structures to design Lean 2-layer RBMs）</news:title>
   <news:publication_date>2026-05-16T00:13:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690628</loc>
  <lastmod>2026-05-16T00:13:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多視点二重タスク再帰注意モデルによる左心房と心房瘢痕の同時セグメンテーション（Multiview Two-Task Recursive Attention Model for Left Atrium and Atrial Scars Segmentation）</news:title>
   <news:publication_date>2026-05-16T00:13:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690626</loc>
  <lastmod>2026-05-16T00:12:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間戦略を取り込むマルチエージェント深層強化学習（Multi-Agent Deep Reinforcement Learning with Human Strategies）</news:title>
   <news:publication_date>2026-05-16T00:12:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690624</loc>
  <lastmod>2026-05-16T00:11:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低温下でのR5912-20Mod光電子増倍管の特性評価（Cryogenic R5912-20Mod Photomultiplier Tube Characterization for the ProtoDUNE Dual Phase Detector）</news:title>
   <news:publication_date>2026-05-16T00:11:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690622</loc>
  <lastmod>2026-05-16T00:11:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一方分類（One-Sided Classification）とスペクトル解析の実務応用（A One-Sided Classification Toolkit with Applications in the Analysis of Spectroscopy Data）</news:title>
   <news:publication_date>2026-05-16T00:11:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690620</loc>
  <lastmod>2026-05-16T00:11:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心電図における期外収縮（PVC）検出に向けたDenseNet＋SPPの提案（Detection of Premature Ventricular Contractions Using Densely Connected Deep Convolutional Neural Network with Spatial Pyramid Pooling Layer）</news:title>
   <news:publication_date>2026-05-16T00:11:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690618</loc>
  <lastmod>2026-05-15T23:20:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平均作用素に基づくアルゴリズムの拡張（An Extension of Averaged-Operator-Based Algorithms）</news:title>
   <news:publication_date>2026-05-15T23:20:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690616</loc>
  <lastmod>2026-05-15T23:19:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話者検証からの転移学習によるマルチ話者音声合成（Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis）</news:title>
   <news:publication_date>2026-05-15T23:19:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690614</loc>
  <lastmod>2026-05-15T23:19:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロジスティックアンサンブルモデル（Logistic Ensemble Models）</news:title>
   <news:publication_date>2026-05-15T23:19:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690612</loc>
  <lastmod>2026-05-15T23:18:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>埋め込みマイクロコントローラ上での低消費電力CNNによる早期てんかん発作検出（Early Seizure Detection with an Energy-Efﬁcient Convolutional Neural Network on an Implantable Microcontroller）</news:title>
   <news:publication_date>2026-05-15T23:18:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690610</loc>
  <lastmod>2026-05-15T23:18:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D MR-TRUS 画像登録のための深層類似度学習（Learning Deep Similarity Metric for 3D MR-TRUS Registration）</news:title>
   <news:publication_date>2026-05-15T23:18:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690608</loc>
  <lastmod>2026-05-15T23:17:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無条件単語生成のための深い状態空間モデル（Deep State Space Models for Unconditional Word Generation）</news:title>
   <news:publication_date>2026-05-15T23:17:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690606</loc>
  <lastmod>2026-05-15T23:17:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Q-アンサンブルとモデルベース探索の統合による情報に基づく探索強化（Combining Model-Free Q-Ensembles and Model-Based Approaches for Informed Exploration）</news:title>
   <news:publication_date>2026-05-15T23:17:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690604</loc>
  <lastmod>2026-05-15T22:26:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタ学習による確率的勾配MCMCの自動設計（Meta-Learning for Stochastic Gradient MCMC）</news:title>
   <news:publication_date>2026-05-15T22:26:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690602</loc>
  <lastmod>2026-05-15T22:17:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>47-Tuc球状星団の中心暗黒質量に対するソリトン解とAxiverseの含意（A Soliton Solution for the Central Dark Masses in 47-Tuc Globular Cluster and Implications for the Axiverse）</news:title>
   <news:publication_date>2026-05-15T22:17:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690600</loc>
  <lastmod>2026-05-15T22:17:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wasserstein勾配流による近似推論（Approximate inference with Wasserstein gradient flows）</news:title>
   <news:publication_date>2026-05-15T22:17:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690598</loc>
  <lastmod>2026-05-15T22:16:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GAN訓練における単純平均化の有効性（THE UNUSUAL EFFECTIVENESS OF AVERAGING IN GAN TRAINING）</news:title>
   <news:publication_date>2026-05-15T22:16:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690596</loc>
  <lastmod>2026-05-15T22:16:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BNFスタイル表記の実務的解釈と応用可能性（What Does This Notation Mean Anyway? BNF-Style Notation as it is Actually Used）</news:title>
   <news:publication_date>2026-05-15T22:16:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690594</loc>
  <lastmod>2026-05-15T22:16:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在変数の記述力を高めるAutoGen（Improving latent variable descriptiveness with AutoGen）</news:title>
   <news:publication_date>2026-05-15T22:16:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690592</loc>
  <lastmod>2026-05-15T22:15:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>距離に基づく時系列分類のレビュー（A review on distance based time series classification）</news:title>
   <news:publication_date>2026-05-15T22:15:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690590</loc>
  <lastmod>2026-05-15T21:24:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在アルファモデルで学習する取引アルゴリズム（Trading algorithms with learning in latent alpha models）</news:title>
   <news:publication_date>2026-05-15T21:24:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690588</loc>
  <lastmod>2026-05-15T21:23:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウシアン混合モデルとワッサースタイン距離（Gaussian mixture models with Wasserstein distance）</news:title>
   <news:publication_date>2026-05-15T21:23:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690586</loc>
  <lastmod>2026-05-15T21:23:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース確率的ゼロ次最適化とバンディット構造化予測への応用（Sparse Stochastic Zeroth-Order Optimization with an Application to Bandit Structured Prediction）</news:title>
   <news:publication_date>2026-05-15T21:23:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690584</loc>
  <lastmod>2026-05-15T21:22:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ToxicBlendによる毒性化合物の仮想スクリーニング（ToxicBlend: Virtual Screening of Toxic Compounds with Ensemble Predictors）</news:title>
   <news:publication_date>2026-05-15T21:22:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690582</loc>
  <lastmod>2026-05-15T21:22:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話状態表現を組み込んだシーケンス・ツー・シーケンス学習（Sequence-to-Sequence Learning for Task-oriented Dialogue with Dialogue State Representation）</news:title>
   <news:publication_date>2026-05-15T21:22:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690580</loc>
  <lastmod>2026-05-15T21:22:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒンディー英語コードミックスの感情分析におけるアンサンブル手法（An Ensemble Model for Sentiment Analysis of Hindi-English Code-Mixed Data）</news:title>
   <news:publication_date>2026-05-15T21:22:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690578</loc>
  <lastmod>2026-05-15T21:21:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>V-CNN：データ可視化でCNNを他分野へ拡張する手法（V-CNN: When Convolutional Neural Network encounters Data Visualization）</news:title>
   <news:publication_date>2026-05-15T21:21:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690576</loc>
  <lastmod>2026-05-15T20:30:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>U-SegNet: MRI脳組織自動セグメンテーションの実用化に向けたハイブリッドFCN（U-SEGNET: FULLY CONVOLUTIONAL NEURAL NETWORK BASED AUTOMATED BRAIN TISSUE SEGMENTATION TOOL）</news:title>
   <news:publication_date>2026-05-15T20:30:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690574</loc>
  <lastmod>2026-05-15T20:30:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランキングの頑健性と文書操作への耐性（Ranking Robustness Under Adversarial Document Manipulations）</news:title>
   <news:publication_date>2026-05-15T20:30:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690572</loc>
  <lastmod>2026-05-15T20:30:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音響シーン分類におけるSample DropoutとマルチスケールDenseNetの実践的意義（Sample Dropout for Audio Scene Classification Using Multi-Scale Dense Connected Convolutional Neural Network）</news:title>
   <news:publication_date>2026-05-15T20:30:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690570</loc>
  <lastmod>2026-05-15T20:29:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>四元数再帰型ニューラルネットワーク（Quaternion Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-05-15T20:29:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690568</loc>
  <lastmod>2026-05-15T20:29:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床MRI灌流マップの強化とデータ駆動型補完マップによる梗塞転帰予測（Enhancing clinical MRI Perfusion maps with data-driven maps of complementary nature for lesion outcome prediction）</news:title>
   <news:publication_date>2026-05-15T20:29:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690566</loc>
  <lastmod>2026-05-15T20:28:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーモアと名言を同じネットで生成する知識統合（Knowledge Amalgam: Generating Jokes and Quotes Together）</news:title>
   <news:publication_date>2026-05-15T20:28:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690564</loc>
  <lastmod>2026-05-15T20:28:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意深いクロスモーダルパラトープ予測（Attentive cross-modal paratope prediction）</news:title>
   <news:publication_date>2026-05-15T20:28:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690562</loc>
  <lastmod>2026-05-15T19:37:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モノディスパース対ポリディスパース超音波コントラスト剤（Monodisperse versus polydisperse ultrasound contrast agents: nonlinear response, sensitivity, and deep tissue imaging potential）</news:title>
   <news:publication_date>2026-05-15T19:37:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690560</loc>
  <lastmod>2026-05-15T19:27:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン間の感情分析を結ぶ埋め込み投影（Projecting Embeddings for Domain Adaptation: Joint Modeling of Sentiment Analysis in Diverse Domains）</news:title>
   <news:publication_date>2026-05-15T19:27:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690558</loc>
  <lastmod>2026-05-15T19:27:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速回転スパース符号化（Fast Rotational Sparse Coding）</news:title>
   <news:publication_date>2026-05-15T19:27:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690556</loc>
  <lastmod>2026-05-15T19:25:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MSplit LBIによる特徴選択と密な推定の同時実現（MSplit LBI: Realizing Feature Selection and Dense Estimation Simultaneously）</news:title>
   <news:publication_date>2026-05-15T19:25:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690554</loc>
  <lastmod>2026-05-15T19:25:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地上ロボットの走破性を深層学習で読む（DeepTerramechanics: Terrain Classification and Slip Estimation for Ground Robots via Deep Learning）</news:title>
   <news:publication_date>2026-05-15T19:25:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690552</loc>
  <lastmod>2026-05-15T19:25:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スタイルをまたぐ翻訳と文体制御を同時に学習する手法（Multi-Task Neural Models for Translating Between Styles Within and Across Languages）</news:title>
   <news:publication_date>2026-05-15T19:25:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690550</loc>
  <lastmod>2026-05-15T19:25:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>社会物理学におけるエージェントベースモデル（Agent-Based Models in Social Physics）</news:title>
   <news:publication_date>2026-05-15T19:25:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690548</loc>
  <lastmod>2026-05-15T18:33:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ・トランスダクションゲームによるマルチターゲット追跡（A Graph Transduction Game for Multi-target Tracking）</news:title>
   <news:publication_date>2026-05-15T18:33:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690546</loc>
  <lastmod>2026-05-15T18:33:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReLUモデル下で勾配法がいつマックスマージン分類器に収束するか（When Will Gradient Methods Converge to Max-margin Classifier under ReLU Models?）</news:title>
   <news:publication_date>2026-05-15T18:33:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690544</loc>
  <lastmod>2026-05-15T18:32:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き系列処理のためのFocused Hierarchical RNN（Focused Hierarchical RNNs for Conditional Sequence Processing）</news:title>
   <news:publication_date>2026-05-15T18:32:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690542</loc>
  <lastmod>2026-05-15T18:32:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>微分可能な合成カーネル学習によるガウス過程の刷新（Differentiable Compositional Kernel Learning for Gaussian Processes）</news:title>
   <news:publication_date>2026-05-15T18:32:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690540</loc>
  <lastmod>2026-05-15T18:31:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低リソース言語に対する単一Transformerによる多言語エンドツーエンド音声認識（Multilingual End-to-End Speech Recognition with A Single Transformer on Low-Resource Languages）</news:title>
   <news:publication_date>2026-05-15T18:31:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690538</loc>
  <lastmod>2026-05-15T18:31:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応型ロバストMPCによる自動車レーンキーピング（Adaptive MPC for Autonomous Lane Keeping）</news:title>
   <news:publication_date>2026-05-15T18:31:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690536</loc>
  <lastmod>2026-05-15T18:30:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非負表現に基づく分類の実用性（Nonnegative Representation based Classification）</news:title>
   <news:publication_date>2026-05-15T18:30:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690534</loc>
  <lastmod>2026-05-15T17:39:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多相流パターン予測におけるSVM応用（Support Vector Machine Application for Multiphase Flow Pattern Prediction）</news:title>
   <news:publication_date>2026-05-15T17:39:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690532</loc>
  <lastmod>2026-05-15T17:39:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エネルギー制約下の深層ニューラルネットワーク圧縮（Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and Layer Input Masking）</news:title>
   <news:publication_date>2026-05-15T17:39:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690530</loc>
  <lastmod>2026-05-15T17:38:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーボリック空間におけるテキスト埋め込み（Embedding Text in Hyperbolic Spaces）</news:title>
   <news:publication_date>2026-05-15T17:38:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690528</loc>
  <lastmod>2026-05-15T17:38:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習によるタービン翼の圧力予測 (Pressure Predictions of Turbine Blades with Deep Learning)</news:title>
   <news:publication_date>2026-05-15T17:38:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690526</loc>
  <lastmod>2026-05-15T17:38:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚に基づくパラフレーズ抽出（iParaphrasing: Extracting Visually Grounded Paraphrases via an Image）</news:title>
   <news:publication_date>2026-05-15T17:38:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690524</loc>
  <lastmod>2026-05-15T17:37:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超大規模特徴選択のためのMISSION（MISSION: Feature Selection via Sketching）</news:title>
   <news:publication_date>2026-05-15T17:37:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690522</loc>
  <lastmod>2026-05-15T17:37:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様なオンライン特徴選択（Diverse Online Feature Selection）</news:title>
   <news:publication_date>2026-05-15T17:37:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690520</loc>
  <lastmod>2026-05-15T16:46:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>比較不可能コーパスから学ぶ多言語トピック（Learning Multilingual Topics from Incomparable Corpora）</news:title>
   <news:publication_date>2026-05-15T16:46:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690518</loc>
  <lastmod>2026-05-15T16:35:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NES音楽データベースが示す「作曲」と「演奏表現」の分離可能性（The NES Music Database: A multi-instrumental dataset with expressive performance attributes）</news:title>
   <news:publication_date>2026-05-15T16:35:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690516</loc>
  <lastmod>2026-05-15T16:35:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スニペット（パッチ）学習を“説明”から理解する（UNDERSTANDING PATCH-BASED LEARNING BY EXPLAINING PREDICTIONS）</news:title>
   <news:publication_date>2026-05-15T16:35:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690514</loc>
  <lastmod>2026-05-15T16:34:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化出力予測の高速化学習（Learning to Speed Up Structured Output Prediction）</news:title>
   <news:publication_date>2026-05-15T16:34:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690512</loc>
  <lastmod>2026-05-15T16:34:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>戻り値分布を使った探索の可能性（The Potential of the Return Distribution for Exploration in RL）</news:title>
   <news:publication_date>2026-05-15T16:34:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690510</loc>
  <lastmod>2026-05-15T16:34:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク駆動型生成モデルによる教師なしドメイン適応とX線画像セグメンテーション（Task Driven Generative Modeling for Unsupervised Domain Adaptation: Application to X-ray Image Segmentation）</news:title>
   <news:publication_date>2026-05-15T16:34:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690508</loc>
  <lastmod>2026-05-15T16:33:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔モーフィング攻撃検出に向けた頑健で高精度なニューラルネットワーク（Accurate and Robust Neural Networks for Security Related Applications Exampled by Face Morphing Attacks）</news:title>
   <news:publication_date>2026-05-15T16:33:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690506</loc>
  <lastmod>2026-05-15T15:42:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚分析データベースのための物理表現に基づく述語最適化（Physical Representation-based Predicate Optimization for a Visual Analytics Database）</news:title>
   <news:publication_date>2026-05-15T15:42:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690504</loc>
  <lastmod>2026-05-15T15:42:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NeuroNetによる脳画像セグメンテーションの統合化（NeuroNet: Fast and Robust Reproduction of Multiple Brain Image Segmentation Pipelines）</news:title>
   <news:publication_date>2026-05-15T15:42:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690502</loc>
  <lastmod>2026-05-15T15:41:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>環境一般化が証明された制御方策の学習（PAC-Bayes Control: Learning Policies that Provably Generalize to Novel Environments）</news:title>
   <news:publication_date>2026-05-15T15:41:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690500</loc>
  <lastmod>2026-05-15T15:41:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローカル説明手法の感度に関する考察（A NOTE ABOUT: LOCAL EXPLANATION METHODS FOR DEEP NEURAL NETWORKS LACK SENSITIVITY TO PARAMETER VALUES）</news:title>
   <news:publication_date>2026-05-15T15:41:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690498</loc>
  <lastmod>2026-05-15T15:40:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ブロックモデルの普遍性（Universality of the stochastic block model）</news:title>
   <news:publication_date>2026-05-15T15:40:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690496</loc>
  <lastmod>2026-05-15T15:40:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群れ行動に学ぶ確率最適化の高速化（Swarming for Faster Convergence in Stochastic Optimization）</news:title>
   <news:publication_date>2026-05-15T15:40:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690494</loc>
  <lastmod>2026-05-15T15:40:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D畳み込みニューラルネットワークによる機能的コネクトームの分類（3D Convolutional Neural Networks for Classification of Functional Connectomes）</news:title>
   <news:publication_date>2026-05-15T15:40:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690492</loc>
  <lastmod>2026-05-15T14:48:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半パラメトリックBARTによる異質な治療効果評価手法（A semiparametric modeling approach using Bayesian Additive Regression Trees with an application to evaluate heterogeneous treatment effects）</news:title>
   <news:publication_date>2026-05-15T14:48:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690490</loc>
  <lastmod>2026-05-15T14:48:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>訓練中に重みの大部分を「追わない」学習法が示す意義（Full deep neural network training on a pruned weight budget）</news:title>
   <news:publication_date>2026-05-15T14:48:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690488</loc>
  <lastmod>2026-05-15T14:48:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報パーコレーション法のグラフ上再構成問題への応用 (Application of information-percolation method to reconstruction problems on graphs)</news:title>
   <news:publication_date>2026-05-15T14:48:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690486</loc>
  <lastmod>2026-05-15T14:47:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構文木へ一直線：ニューラル合成距離による句構造解析（Straight to the Tree: Constituency Parsing with Neural Syntactic Distance）</news:title>
   <news:publication_date>2026-05-15T14:47:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690484</loc>
  <lastmod>2026-05-15T14:47:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的事例に対する防御研究の俯瞰（Defense Against the Dark Arts: An overview of adversarial example security research and future research directions）</news:title>
   <news:publication_date>2026-05-15T14:47:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690482</loc>
  <lastmod>2026-05-15T14:47:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像予測のための表現分解と分離学習（Learning to Decompose and Disentangle Representations for Video Prediction）</news:title>
   <news:publication_date>2026-05-15T14:47:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690480</loc>
  <lastmod>2026-05-15T14:47:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似学習による保証付きモデル予測制御（Learning an Approximate Model Predictive Controller with Guarantees）</news:title>
   <news:publication_date>2026-05-15T14:47:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690478</loc>
  <lastmod>2026-05-15T13:55:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化プリマル・デュアル法と適応ステップ幅（Randomized Primal-Dual Methods with Adaptive Step Sizes）</news:title>
   <news:publication_date>2026-05-15T13:55:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690476</loc>
  <lastmod>2026-05-15T13:55:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補完データで全天マップを鮮明化する機械学習手法（Sharpening up Galactic all-sky maps with complementary data: A machine learning approach）</news:title>
   <news:publication_date>2026-05-15T13:55:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690474</loc>
  <lastmod>2026-05-15T13:55:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音響生成におけるオートエンコーダの実用比較（Autoencoders for music sound modeling: a comparison of linear, shallow, deep, recurrent and variational models）</news:title>
   <news:publication_date>2026-05-15T13:55:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690472</loc>
  <lastmod>2026-05-15T13:54:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協力を促す適応的メカニズム設計（Adaptive Mechanism Design: Learning to Promote Cooperation）</news:title>
   <news:publication_date>2026-05-15T13:54:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690470</loc>
  <lastmod>2026-05-15T13:54:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子分解に基づく通信効率化学習（Atomo: Communication-efficient Learning via Atomic Sparsification）</news:title>
   <news:publication_date>2026-05-15T13:54:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690468</loc>
  <lastmod>2026-05-15T13:54:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セマンティックに選択されたデータ増強による軽量人物再識別（Semantically Selective Augmentation for Deep Compact Person Re-Identification）</news:title>
   <news:publication_date>2026-05-15T13:54:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690466</loc>
  <lastmod>2026-05-15T13:53:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープスペックル相関：散乱媒体越えのスケーラブルなイメージング（Deep speckle correlation: a deep learning approach towards scalable imaging through scattering media）</news:title>
   <news:publication_date>2026-05-15T13:53:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690464</loc>
  <lastmod>2026-05-15T13:02:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓MRI系列における動き推定とセグメンテーションの共同学習（Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image Sequences）</news:title>
   <news:publication_date>2026-05-15T13:02:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690462</loc>
  <lastmod>2026-05-15T13:02:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CT画像に現実的な肺結節を生成してセグメンテーションを強化する技術（CT-Realistic Lung Nodule Simulation from 3D Conditional Generative Adversarial Networks for Robust Lung Segmentation）</news:title>
   <news:publication_date>2026-05-15T13:02:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690460</loc>
  <lastmod>2026-05-15T13:01:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元データ強化（High Dimensional Data Enrichment: Interpretable, Fast, and Data-Efficient）</news:title>
   <news:publication_date>2026-05-15T13:01:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690458</loc>
  <lastmod>2026-05-15T13:01:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メールの追跡（トラッキング）を見抜く機械学習手法（Robust Identification of Email Tracking: A Machine Learning Approach）</news:title>
   <news:publication_date>2026-05-15T13:01:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690456</loc>
  <lastmod>2026-05-15T13:00:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所的な平行移動不変構造を持つ信号の適応的雑音除去（Adaptive Denoising of Signals with Local Shift-Invariant Structure）</news:title>
   <news:publication_date>2026-05-15T13:00:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690454</loc>
  <lastmod>2026-05-15T13:00:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制御された悪天候画像データセットとそのベースライン（Baselines and a datasheet for the Cerema AWP dataset）</news:title>
   <news:publication_date>2026-05-15T13:00:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690452</loc>
  <lastmod>2026-05-15T13:00:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数非開示データをまたいだ予測の集約とプライバシー保全（Aggregating Predictions on Multiple Non-disclosed Datasets using Conformal Prediction）</news:title>
   <news:publication_date>2026-05-15T13:00:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690450</loc>
  <lastmod>2026-05-15T12:09:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在空間表現による形状解析と学習（Latent Space Representation for Shape Analysis and Learning）</news:title>
   <news:publication_date>2026-05-15T12:09:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690448</loc>
  <lastmod>2026-05-15T12:08:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>屋内照明推定の学習法（Learning to Estimate Indoor Lighting from 3D Objects）</news:title>
   <news:publication_date>2026-05-15T12:08:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690446</loc>
  <lastmod>2026-05-15T12:08:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形時間論理（LTL）からの学習手法の実務的意義（Learning Linear Temporal Properties）</news:title>
   <news:publication_date>2026-05-15T12:08:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690444</loc>
  <lastmod>2026-05-15T12:07:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>系外惑星大気スペクトル解析のための教師あり機械学習（Supervised Machine Learning for Analysing Spectra of Exoplanetary Atmospheres）</news:title>
   <news:publication_date>2026-05-15T12:07:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690442</loc>
  <lastmod>2026-05-15T12:07:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>k-NN分類のための高速で簡単な回帰手法（A Fast and Easy Regression Technique for k-NN Classification Without Using Negative Pairs）</news:title>
   <news:publication_date>2026-05-15T12:07:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690440</loc>
  <lastmod>2026-05-15T12:07:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フィードフォワードニューラルネットワークにおけるローカリスト表現の出現条件（When and where do feed-forward neural networks learn localist representations?）</news:title>
   <news:publication_date>2026-05-15T12:07:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690438</loc>
  <lastmod>2026-05-15T12:07:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルを分割して速さで差をつける学習法（GEAR TRAINING: A NEW WAY TO IMPLEMENT HIGH-PERFORMANCE MODEL-PARALLEL TRAINING）</news:title>
   <news:publication_date>2026-05-15T12:07:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690436</loc>
  <lastmod>2026-05-15T11:15:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多言語シーン文字認識における疎オートエンコーダを用いた効率的局所特徴表現（Multilingual Scene Character Recognition System using Sparse Auto-Encoder for Efficient Local Features Representation in Bag of Features）</news:title>
   <news:publication_date>2026-05-15T11:15:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690434</loc>
  <lastmod>2026-05-15T11:15:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Projective Splittingの収束率解析（Convergence Rates for Projective Splitting）</news:title>
   <news:publication_date>2026-05-15T11:15:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690432</loc>
  <lastmod>2026-05-15T11:15:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜の視神経乳頭（optic disc）領域をcGANで自動抽出する手法（Retinal Optic Disc Segmentation using Conditional Generative Adversarial Network）</news:title>
   <news:publication_date>2026-05-15T11:15:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690430</loc>
  <lastmod>2026-05-15T11:14:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混雑状況における深度ベースの6次元姿勢推定と共同登録（Multi-Task Deep Networks for Depth-Based 6D Object Pose and Joint Registration in Crowd Scenarios）</news:title>
   <news:publication_date>2026-05-15T11:14:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690428</loc>
  <lastmod>2026-05-15T11:14:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二重パターン学習ネットワークの提案（Dual Pattern Learning Networks by Empirical Dual Prediction Risk Minimization）</news:title>
   <news:publication_date>2026-05-15T11:14:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690426</loc>
  <lastmod>2026-05-15T11:14:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳波信号のフラクタル性とマルチフラクタル性の計測意義（Fractal and multifractal properties of electrographic recordings of human brain activity）</news:title>
   <news:publication_date>2026-05-15T11:14:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690424</loc>
  <lastmod>2026-05-15T11:14:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>調査データからの日常的な通勤・通学往復のマルチタスク学習（Multi-task learning of daily work and study round-trips from survey data）</news:title>
   <news:publication_date>2026-05-15T11:14:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690422</loc>
  <lastmod>2026-05-15T10:22:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SDN向けフロー基盤の多段階ハイブリッド侵入検知（An Efficient Flow-based Multi-level Hybrid Intrusion Detection System for Software-Defined Networks）</news:title>
   <news:publication_date>2026-05-15T10:22:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690420</loc>
  <lastmod>2026-05-15T10:22:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多述語間相互作用を距離に依存せず捉える日本語述語項構造解析（Distance-Free Modeling of Multi-Predicate Interactions in End-to-End Japanese Predicate-Argument Structure Analysis）</news:title>
   <news:publication_date>2026-05-15T10:22:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690418</loc>
  <lastmod>2026-05-15T10:22:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Kronecker-factored Eigenbasisによる高速近似ナチュラル勾配法（Fast Approximate Natural Gradient Descent in a Kronecker-factored Eigenbasis）</news:title>
   <news:publication_date>2026-05-15T10:22:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690416</loc>
  <lastmod>2026-05-15T10:21:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>産業向け物体検出と追跡の評価基準と改良相関フィルタ（Object Detection and Tracking Benchmark in Industry Based on Improved Correlation Filter）</news:title>
   <news:publication_date>2026-05-15T10:21:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690414</loc>
  <lastmod>2026-05-15T10:21:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タンパク質ガンマターン予測におけるInception Capsule Networkの応用（Improving Protein Gamma-Turn Prediction Using Inception Capsule Networks）</news:title>
   <news:publication_date>2026-05-15T10:21:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690412</loc>
  <lastmod>2026-05-15T10:21:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地理空間ベクトル多角形の分類における深層学習（Deep Learning for Classification Tasks on Geospatial Vector Polygons）</news:title>
   <news:publication_date>2026-05-15T10:21:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690410</loc>
  <lastmod>2026-05-15T10:21:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模並列ビデオネットワーク（Massively Parallel Video Networks）</news:title>
   <news:publication_date>2026-05-15T10:21:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690408</loc>
  <lastmod>2026-05-15T09:30:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成パーフュージョンマップによるDSC-MRI欠損検出の深層学習（Synthetic Perfusion Maps: Imaging Perfusion Deficits in DSC-MRI with Deep Learning）</news:title>
   <news:publication_date>2026-05-15T09:30:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690406</loc>
  <lastmod>2026-05-15T09:29:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>曖昧な指示を解くマルチモーダルGAN（A Multimodal Classifier Generative Adversarial Network for Carry and Place Tasks from Ambiguous Language Instructions）</news:title>
   <news:publication_date>2026-05-15T09:29:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690404</loc>
  <lastmod>2026-05-15T09:29:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>明示的正則化の代わりにデータ拡張を使う（Data augmentation instead of explicit regularization）</news:title>
   <news:publication_date>2026-05-15T09:29:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690402</loc>
  <lastmod>2026-05-15T09:28:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタ継続学習の要点を経営視点で読む（Meta Continual Learning）</news:title>
   <news:publication_date>2026-05-15T09:28:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690400</loc>
  <lastmod>2026-05-15T09:28:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン知識フリーの機械学習による解析接続（Analytic continuation via domain-knowledge free machine learning）</news:title>
   <news:publication_date>2026-05-15T09:28:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690398</loc>
  <lastmod>2026-05-15T09:28:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数局所サンプラーを組み合わせる適応MCMC（Adaptive MCMC via Combining Local Samplers）</news:title>
   <news:publication_date>2026-05-15T09:28:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690396</loc>
  <lastmod>2026-05-15T09:28:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ的モデル不可知メタラーニングの要点解説（Bayesian Model-Agnostic Meta-Learning）</news:title>
   <news:publication_date>2026-05-15T09:28:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690394</loc>
  <lastmod>2026-05-15T08:36:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>候補群の依存性とアルゴリズム依存性を同時に扱う一般化誤差評価（Chaining Mutual Information and Tightening Generalization Bounds）</news:title>
   <news:publication_date>2026-05-15T08:36:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690392</loc>
  <lastmod>2026-05-15T08:27:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相のみのホログラムのJPEG圧縮と深層学習によるアーティファクト低減（Compression of phase-only holograms with JPEG standard and deep learning）</news:title>
   <news:publication_date>2026-05-15T08:27:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690390</loc>
  <lastmod>2026-05-15T08:26:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Greybox Fuzzingを文脈型バンディット問題として扱う（Greybox fuzzing as a contextual bandits problem）</news:title>
   <news:publication_date>2026-05-15T08:26:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690388</loc>
  <lastmod>2026-05-15T08:26:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタ学習の自動アーキテクチャ探索（Automated Gradient Based Meta Learner Search）</news:title>
   <news:publication_date>2026-05-15T08:26:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690386</loc>
  <lastmod>2026-05-15T08:25:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数データセット横断の人物再識別と類似性保持生成対向ネットワーク（Cross-dataset Person Re-Identification Using Similarity Preserved Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-15T08:25:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690384</loc>
  <lastmod>2026-05-15T08:25:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カプセルネットワークを用いた画像合成のGANアーキテクチャ（Generative Adversarial Network Architectures For Image Synthesis Using Capsule Networks）</news:title>
   <news:publication_date>2026-05-15T08:25:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690382</loc>
  <lastmod>2026-05-15T08:25:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈認識型ポリシー再利用（Context-Aware Policy Reuse）</news:title>
   <news:publication_date>2026-05-15T08:25:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690380</loc>
  <lastmod>2026-05-15T07:34:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子データに対する微分幾何学ベースの幾何学的学習（DG-GL: Differential geometry based geometric learning of molecular datasets）</news:title>
   <news:publication_date>2026-05-15T07:34:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690378</loc>
  <lastmod>2026-05-15T07:33:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像からの物体オクルージョン境界検出の深層手法（DOOBNet: Deep Object Occlusion Boundary Detection from an Image）</news:title>
   <news:publication_date>2026-05-15T07:33:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690376</loc>
  <lastmod>2026-05-15T07:33:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク幅が大規模バッチ学習性能に与える影響（The Effect of Network Width on the Performance of Large-batch Training）</news:title>
   <news:publication_date>2026-05-15T07:33:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690374</loc>
  <lastmod>2026-05-15T07:33:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次元Dzyaloshinskii–Moriya強磁性体への機械学習応用（Machine Learning Application to Two-Dimensional Dzyaloshinskii-Moriya Ferromagnets）</news:title>
   <news:publication_date>2026-05-15T07:33:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690372</loc>
  <lastmod>2026-05-15T07:33:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平滑化解析による低ランク手法の評価（Smoothed analysis of the low-rank approach for smooth semidefinite programs）</news:title>
   <news:publication_date>2026-05-15T07:33:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690370</loc>
  <lastmod>2026-05-15T07:32:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークの状態空間表現（State Space Representations of Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-15T07:32:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690368</loc>
  <lastmod>2026-05-15T07:32:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>絶滅危機言語Grikoの品詞タグ付け資源と評価（Part-of-Speech Tagging on an Endangered Language: a Parallel Griko-Italian Resource）</news:title>
   <news:publication_date>2026-05-15T07:32:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690366</loc>
  <lastmod>2026-05-15T06:41:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈付き形態変化のための構造化変分オートエンコーダ（A Structured Variational Autoencoder for Contextual Morphological Inflection）</news:title>
   <news:publication_date>2026-05-15T06:41:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690364</loc>
  <lastmod>2026-05-15T06:41:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同形語による形態曖昧性を無監督で解消する手法（Unsupervised Disambiguation of Syncretism in Inflected Lexicons）</news:title>
   <news:publication_date>2026-05-15T06:41:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690362</loc>
  <lastmod>2026-05-15T06:40:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応型セッションベース推薦のためのコンテキストツリー（Context Tree for Adaptive Session-based Recommendation）</news:title>
   <news:publication_date>2026-05-15T06:40:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690360</loc>
  <lastmod>2026-05-15T06:40:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Smallify: 学習中にネットワークサイズを決める（Smallify: Learning Network Size while Training）</news:title>
   <news:publication_date>2026-05-15T06:40:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690358</loc>
  <lastmod>2026-05-15T06:39:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回答埋め込みを学習するVisual QA（Learning Answer Embeddings for Visual Question Answering）</news:title>
   <news:publication_date>2026-05-15T06:39:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690356</loc>
  <lastmod>2026-05-15T06:39:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスデータセット適応によるVisual QAの汎化（Cross-Dataset Adaptation for Visual Question Answering）</news:title>
   <news:publication_date>2026-05-15T06:39:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690354</loc>
  <lastmod>2026-05-15T06:39:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層生成モデルを用いた確率的地震波形インバージョン（Stochastic Seismic Waveform Inversion using Generative Adversarial Networks as a Geological Prior）</news:title>
   <news:publication_date>2026-05-15T06:39:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690352</loc>
  <lastmod>2026-05-15T05:47:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>建設現場の油・重金属汚染土壌のバイオレメディエーション事例（Bioremediation of oil and heavy metal contaminated soil in construction sites: a case study of using bioventing-biosparging and phytoextraction techniques）</news:title>
   <news:publication_date>2026-05-15T05:47:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690350</loc>
  <lastmod>2026-05-15T05:47:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>噂（Rumour）検証のためのオールインワン・マルチタスク学習（All-in-one: Multi-task Learning for Rumour Verification）</news:title>
   <news:publication_date>2026-05-15T05:47:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690348</loc>
  <lastmod>2026-05-15T05:46:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中国語のゼロ代名詞解決に深層強化学習を使う意義（Deep Reinforcement Learning for Chinese Zero Pronoun Resolution）</news:title>
   <news:publication_date>2026-05-15T05:46:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690346</loc>
  <lastmod>2026-05-15T05:46:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型乱流モデルのための深層ニューラルネットワーク（Deep Neural Networks for Data-Driven Turbulence Models）</news:title>
   <news:publication_date>2026-05-15T05:46:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690344</loc>
  <lastmod>2026-05-15T05:46:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デコンボリューションを用いたグローバルデコーディングによる機械翻訳（Deconvolution-Based Global Decoding for Neural Machine Translation）</news:title>
   <news:publication_date>2026-05-15T05:46:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690342</loc>
  <lastmod>2026-05-15T05:45:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無監督動画間変換（Unsupervised Video-to-Video Translation）</news:title>
   <news:publication_date>2026-05-15T05:45:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690340</loc>
  <lastmod>2026-05-15T05:45:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>法務・規制文書のための自然言語処理と情報抽出（LexNLP: Natural language processing and information extraction for legal and regulatory texts）</news:title>
   <news:publication_date>2026-05-15T05:45:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690338</loc>
  <lastmod>2026-05-15T04:54:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>散逸性理論による確率的分散削減の加速化（Dissipativity Theory for Accelerating Stochastic Variance Reduction）</news:title>
   <news:publication_date>2026-05-15T04:54:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690336</loc>
  <lastmod>2026-05-15T04:54:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス確率的グラフィカルモデルの識別可能性（Identifiability in Gaussian Graphical Models）</news:title>
   <news:publication_date>2026-05-15T04:54:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690334</loc>
  <lastmod>2026-05-15T04:54:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>選ばれた個体の共分散は景観のヘッセ行列の逆に近づく（On the Covariance-Hessian Relation in Evolution Strategies）</news:title>
   <news:publication_date>2026-05-15T04:54:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690332</loc>
  <lastmod>2026-05-15T04:53:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>鉛管探索のための能動的除去（ActiveRemediation: The Search for Lead Pipes in Flint, Michigan）</news:title>
   <news:publication_date>2026-05-15T04:53:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690330</loc>
  <lastmod>2026-05-15T04:53:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文字ベースのBiLSTM+CRFによる疾患固有表現抽出（Neural Disease Named Entity Extraction with Character-based BiLSTM+CRF in Japanese Medical Text）</news:title>
   <news:publication_date>2026-05-15T04:53:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690328</loc>
  <lastmod>2026-05-15T04:53:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>社会的環境における深層好奇心ループ（Deep Curiosity Loops in Social Environments）</news:title>
   <news:publication_date>2026-05-15T04:53:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690326</loc>
  <lastmod>2026-05-15T04:52:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付きノイズ対比推定による非正規化モデルの推定（Conditional Noise-Contrastive Estimation of Unnormalised Models）</news:title>
   <news:publication_date>2026-05-15T04:52:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690324</loc>
  <lastmod>2026-05-15T04:01:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外科トレーニングの「視覚の超現実化」—現実手術映像を模した無対画像変換（Improving Surgical Training Phantoms by Hyperrealism: Deep Unpaired Image-to-Image Translation from Real Surgeries）</news:title>
   <news:publication_date>2026-05-15T04:01:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690322</loc>
  <lastmod>2026-05-15T04:00:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間文脈を取り入れた音声単語埋め込みの学習（Learning Acoustic Word Embeddings with Temporal Context for Query-by-Example Speech Search）</news:title>
   <news:publication_date>2026-05-15T04:00:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690320</loc>
  <lastmod>2026-05-15T04:00:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>森林環境における移植可能なUAV視覚認識（Learning Transferable UAV for Forest Visual Perception）</news:title>
   <news:publication_date>2026-05-15T04:00:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690318</loc>
  <lastmod>2026-05-15T04:00:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VoxelAtlasGANによる心エコーの左心室3Dセグメンテーション（VoxelAtlasGAN: 3D Left Ventricle Segmentation on Echocardiography with Atlas Guided Generation and Voxel-to-voxel Discrimination）</news:title>
   <news:publication_date>2026-05-15T04:00:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690316</loc>
  <lastmod>2026-05-15T03:59:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布的アドバンテージアクタークリティック（Distributional Advantage Actor-Critic）</news:title>
   <news:publication_date>2026-05-15T03:59:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690314</loc>
  <lastmod>2026-05-15T03:59:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習と形式検証の接点（A Survey on the Application of Machine Learning to Formal Verification）</news:title>
   <news:publication_date>2026-05-15T03:59:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690312</loc>
  <lastmod>2026-05-15T03:59:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Implicit Policyによる強化学習の再定義（Implicit Policy for Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-15T03:59:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690310</loc>
  <lastmod>2026-05-15T03:08:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IVUS-Net: 血管内超音波（IVUS）画像の自動セグメンテーションが変える臨床画像処理（IVUS-Net: An Intravascular Ultrasound Segmentation Network）</news:title>
   <news:publication_date>2026-05-15T03:08:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690308</loc>
  <lastmod>2026-05-15T03:08:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軌跡予測のためのスケーラブルなフレームワーク（A Scalable Framework for Trajectory Prediction）</news:title>
   <news:publication_date>2026-05-15T03:08:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690306</loc>
  <lastmod>2026-05-15T03:08:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自由形状マスクに強い画像修復手法の核—Gated Convolution（Free-Form Image Inpainting with Gated Convolution）</news:title>
   <news:publication_date>2026-05-15T03:08:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690304</loc>
  <lastmod>2026-05-15T03:07:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンスレベルの分割に基づくインスタンス検索（Instance Search via Instance Level Segmentation and Feature Representation）</news:title>
   <news:publication_date>2026-05-15T03:07:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690302</loc>
  <lastmod>2026-05-15T03:07:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一RGB画像からの高精度スペクトル超解像（Accurate Spectral Super-resolution from Single RGB Image Using Multi-scale CNN）</news:title>
   <news:publication_date>2026-05-15T03:07:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690300</loc>
  <lastmod>2026-05-15T03:07:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報検索における生成対向ネットワークの基礎と応用（Generative Adversarial Nets for Information Retrieval: Fundamentals and Advances）</news:title>
   <news:publication_date>2026-05-15T03:07:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690298</loc>
  <lastmod>2026-05-15T03:07:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空中手書きで本人を特定する深層ハッシュ化（FMHash: Deep Hashing of In-Air-Handwriting for User Identification）</news:title>
   <news:publication_date>2026-05-15T03:07:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690296</loc>
  <lastmod>2026-05-15T02:16:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間定常性を利用した幾何学的グラフィカルモデル選択（Stationary Geometric Graphical Model Selection）</news:title>
   <news:publication_date>2026-05-15T02:16:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690294</loc>
  <lastmod>2026-05-15T02:15:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブロック単位で作るベイジアンニューラルネットワーク（Building Bayesian Neural Networks with Blocks: On Structure, Interpretability and Uncertainty）</news:title>
   <news:publication_date>2026-05-15T02:15:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690292</loc>
  <lastmod>2026-05-15T02:15:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意見文データによる説明可能な推薦（Explainable Recommendation via Multi-Task Learning in Opinionated Text Data）</news:title>
   <news:publication_date>2026-05-15T02:15:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690290</loc>
  <lastmod>2026-05-15T02:14:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データベース駆動型認知無線ネットワークにおける位置プライバシー保護（Location Privacy Preservation in Database-driven Wireless Cognitive Networks through Encrypted Probabilistic Data Structures）</news:title>
   <news:publication_date>2026-05-15T02:14:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690288</loc>
  <lastmod>2026-05-15T02:14:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>結晶構造から115,000材料の物性を機械学習で予測する意義（Quantitative trends in 8 physical properties of 115000 inorganic compounds gained by machine learning）</news:title>
   <news:publication_date>2026-05-15T02:14:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690286</loc>
  <lastmod>2026-05-15T02:14:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Raschモデルの推定と誤差解析の実用フレームワーク（An Estimation and Analysis Framework for the Rasch Model）</news:title>
   <news:publication_date>2026-05-15T02:14:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690284</loc>
  <lastmod>2026-05-15T02:13:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表示バイアスを介入なしで推定する手法の要点（Consistent Position Bias Estimation without Online Interventions for Learning-to-Rank）</news:title>
   <news:publication_date>2026-05-15T02:13:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690282</loc>
  <lastmod>2026-05-15T01:22:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形スペクトル推定器と位相回復への応用（Linear Spectral Estimators and an Application to Phase Retrieval）</news:title>
   <news:publication_date>2026-05-15T01:22:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690280</loc>
  <lastmod>2026-05-15T01:22:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ表現学習とJumping Knowledgeネットワーク（Representation Learning on Graphs with Jumping Knowledge Networks）</news:title>
   <news:publication_date>2026-05-15T01:22:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690278</loc>
  <lastmod>2026-05-15T01:21:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>星状凸多角形による細胞検出（Cell Detection with Star-convex Polygons）</news:title>
   <news:publication_date>2026-05-15T01:21:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690276</loc>
  <lastmod>2026-05-15T01:21:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク脅威の分類とデータセットの限界（A Taxonomy of Network Threats and the Effect of Current Datasets on Intrusion Detection Systems）</news:title>
   <news:publication_date>2026-05-15T01:21:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690274</loc>
  <lastmod>2026-05-15T01:21:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長文文書での探索学習による読解（Learning to Search in Long Documents Using Document Structure）</news:title>
   <news:publication_date>2026-05-15T01:21:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690272</loc>
  <lastmod>2026-05-15T01:20:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミレニアル世代に形式手法を教える工夫（Engaging Millennials into Learning Formal Methods）</news:title>
   <news:publication_date>2026-05-15T01:20:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690270</loc>
  <lastmod>2026-05-15T01:20:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Second Language Acquisition Modeling: An Ensemble Approach（Second Language Acquisition Modeling: An Ensemble Approach）</news:title>
   <news:publication_date>2026-05-15T01:20:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690268</loc>
  <lastmod>2026-05-15T00:29:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説明可能な決定性MDP（Explainable Deterministic MDPs）</news:title>
   <news:publication_date>2026-05-15T00:29:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690266</loc>
  <lastmod>2026-05-15T00:20:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Field-weighted Factorization MachinesによるCTR予測の改良（Field-weighted Factorization Machines for Click-Through Rate Prediction in Display Advertising）</news:title>
   <news:publication_date>2026-05-15T00:20:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690264</loc>
  <lastmod>2026-05-15T00:19:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造的脳画像を臨床予測に使う―機械学習応用のレビュー（Structural neuroimaging as clinical predictor: a review of machine learning applications）</news:title>
   <news:publication_date>2026-05-15T00:19:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690262</loc>
  <lastmod>2026-05-15T00:19:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化Earleyパーサによる記号文法と時系列データの橋渡し（Generalized Earley Parser: Bridging Symbolic Grammars and Sequence Data for Future Prediction）</news:title>
   <news:publication_date>2026-05-15T00:19:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690260</loc>
  <lastmod>2026-05-15T00:19:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一デモから把持を学ぶ技術（Learning to Grasp from a Single Demonstration）</news:title>
   <news:publication_date>2026-05-15T00:19:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690258</loc>
  <lastmod>2026-05-15T00:19:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>あいまい地域の境界抽出手法（DIR-ST2: Delineation of Imprecise Regions Using Spatio–Temporal–Textual Information）</news:title>
   <news:publication_date>2026-05-15T00:19:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690256</loc>
  <lastmod>2026-05-15T00:18:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知かつ異種の誤差を伴うネットワーク再構築（Reconstructing networks with unknown and heterogeneous errors）</news:title>
   <news:publication_date>2026-05-15T00:18:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690254</loc>
  <lastmod>2026-05-14T23:27:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>直交ランダムフォレストによる因果推論（Orthogonal Random Forest for Causal Inference）</news:title>
   <news:publication_date>2026-05-14T23:27:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690252</loc>
  <lastmod>2026-05-14T23:27:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前知識を組み込むことで前進した前立腺MR多ラベル分割（Autoencoders for Multi-Label Prostate MR Segmentation）</news:title>
   <news:publication_date>2026-05-14T23:27:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690250</loc>
  <lastmod>2026-05-14T23:26:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頑健なセマンティックセグメンテーションとLadder‑DenseNetモデル（Robust Semantic Segmentation with Ladder‑DenseNet Models）</news:title>
   <news:publication_date>2026-05-14T23:26:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690248</loc>
  <lastmod>2026-05-14T23:26:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TAPASによる暗号化環境下での予測高速化（TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service）</news:title>
   <news:publication_date>2026-05-14T23:26:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690246</loc>
  <lastmod>2026-05-14T23:26:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>負荷均衡HetNetにおけるユーザ割当の学習志向クロスエントロピーアプローチ（Learning Oriented Cross-Entropy Approach to User Association in Load-Balanced HetNet）</news:title>
   <news:publication_date>2026-05-14T23:26:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690244</loc>
  <lastmod>2026-05-14T23:26:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Angular Softmax損失を用いたエンドツーエンド話者認証（Angular Softmax Loss for End-to-end Speaker Verification）</news:title>
   <news:publication_date>2026-05-14T23:26:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690242</loc>
  <lastmod>2026-05-14T23:25:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相対的重要度を測るハイブリッド・アプローチ（A hybrid econometric-machine learning approach for relative importance analysis: Prioritizing food policy）</news:title>
   <news:publication_date>2026-05-14T23:25:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690240</loc>
  <lastmod>2026-05-14T22:34:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前知識を取り入れた階層的クラスタリング（Hierarchical Clustering with Prior Knowledge）</news:title>
   <news:publication_date>2026-05-14T22:34:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690238</loc>
  <lastmod>2026-05-14T22:34:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロバスト主成分分析の最適化アルゴリズムの実践的意義（Efficient Optimization Algorithms for Robust Principal Component Analysis and Its Variants）</news:title>
   <news:publication_date>2026-05-14T22:34:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690236</loc>
  <lastmod>2026-05-14T22:34:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤分類コストが不均一かつ不明な場合の拒否付き分類（Abstaining Classification When Error Costs are Unequal and Unknown）</news:title>
   <news:publication_date>2026-05-14T22:34:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690234</loc>
  <lastmod>2026-05-14T22:33:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互結合を考慮した希薄ベイズ学習による方向推定（Direction Finding based on Sparse Bayesian Learning with Mutual Coupling）</news:title>
   <news:publication_date>2026-05-14T22:33:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690232</loc>
  <lastmod>2026-05-14T22:33:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストレッチ回帰（Deterministic Stretchy Regression）</news:title>
   <news:publication_date>2026-05-14T22:33:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690230</loc>
  <lastmod>2026-05-14T22:33:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローレンツモデルによる連続階層の学習（Learning Continuous Hierarchies in the Lorentz Model of Hyperbolic Geometry）</news:title>
   <news:publication_date>2026-05-14T22:33:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690228</loc>
  <lastmod>2026-05-14T22:33:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>茎位置検出と作物・雑草分類による植物特異的処理（Joint Stem Detection and Crop-Weed Classification for Plant-specific Treatment）</news:title>
   <news:publication_date>2026-05-14T22:33:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690226</loc>
  <lastmod>2026-05-14T21:41:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォトメトリック赤方偏移と銀河形態の大規模カタログ化（A catalog of photometric redshift and the distribution of broad galaxy morphologies）</news:title>
   <news:publication_date>2026-05-14T21:41:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690224</loc>
  <lastmod>2026-05-14T21:41:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表形式データの合成とプライバシー保護（Data Synthesis based on Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-14T21:41:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690222</loc>
  <lastmod>2026-05-14T21:40:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>間接的な同所性リンクを持つグラフモデル（A Graph Model with Indirect Co-location Links）</news:title>
   <news:publication_date>2026-05-14T21:40:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690220</loc>
  <lastmod>2026-05-14T21:39:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文化投資と都市の社会経済発展：ジオソーシャルネットワークの視点から（Cultural Investment and Urban Socio-Economic Development: A Geo-Social Network Approach）</news:title>
   <news:publication_date>2026-05-14T21:39:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690218</loc>
  <lastmod>2026-05-14T21:39:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PipeDreamによる高速で効率的なパイプライン並列DNN訓練（PipeDream: Fast and Efficient Pipeline Parallel DNN Training）</news:title>
   <news:publication_date>2026-05-14T21:39:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690216</loc>
  <lastmod>2026-05-14T21:39:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心電図の不整脈自動注釈を行う深層ネットワークの手法（Method to Annotate Arrhythmias by Deep Network）</news:title>
   <news:publication_date>2026-05-14T21:39:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690214</loc>
  <lastmod>2026-05-14T21:39:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮センシング画像による視覚的質問応答（CS-VQA: VISUAL QUESTION ANSWERING WITH COMPRESSIVELY SENSED IMAGES）</news:title>
   <news:publication_date>2026-05-14T21:39:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690212</loc>
  <lastmod>2026-05-14T20:47:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己監督信号による物体発見と検出（Self-supervisory Signals for Object Discovery and Detection）</news:title>
   <news:publication_date>2026-05-14T20:47:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690210</loc>
  <lastmod>2026-05-14T20:37:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>沸騰熱伝達のデータ駆動モデル化（Data-driven modeling for boiling heat transfer: using deep neural networks and high-fidelity simulation results）</news:title>
   <news:publication_date>2026-05-14T20:37:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690208</loc>
  <lastmod>2026-05-14T20:37:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>窓の中身で人を見分ける融合手法の提案（A Content-Based Late Fusion Approach Applied to Pedestrian Detection）</news:title>
   <news:publication_date>2026-05-14T20:37:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690206</loc>
  <lastmod>2026-05-14T20:36:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DSSLIC：深層セマンティック分割に基づく多層画像圧縮（Deep Semantic Segmentation-based Layered Image Compression）</news:title>
   <news:publication_date>2026-05-14T20:36:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690204</loc>
  <lastmod>2026-05-14T20:36:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン無制約サブモジュラ最大化の最適アルゴリズム（An Optimal Algorithm for Online Unconstrained Submodular Maximization）</news:title>
   <news:publication_date>2026-05-14T20:36:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690202</loc>
  <lastmod>2026-05-14T20:35:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>High cadence観測が切り拓く小惑星検出の新領域（Asteroids in the High Cadence Transient Survey）</news:title>
   <news:publication_date>2026-05-14T20:35:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690200</loc>
  <lastmod>2026-05-14T20:35:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Web情報からサイバー攻撃を予測する技術（Discovering Signals from Web Sources to Predict Cyber Attacks）</news:title>
   <news:publication_date>2026-05-14T20:35:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690198</loc>
  <lastmod>2026-05-14T19:44:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化事前関数による強化学習の不確実性制御（Randomized Prior Functions for Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-14T19:44:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690196</loc>
  <lastmod>2026-05-14T19:43:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手術動作の教師なし表現学習—未来予測でモーションを捉える（Unsupervised Learning for Surgical Motion by Learning to Predict the Future）</news:title>
   <news:publication_date>2026-05-14T19:43:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690194</loc>
  <lastmod>2026-05-14T19:42:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>4トン級デモンストレーターによる大規模二相液体アルゴンTPCの実証（A 4 tonne demonstrator for large-scale dual-phase liquid argon time projection chambers）</news:title>
   <news:publication_date>2026-05-14T19:42:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690192</loc>
  <lastmod>2026-05-14T19:42:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュートリノ実験におけるミリチャージ粒子の探索（Millicharged particles in neutrino experiments）</news:title>
   <news:publication_date>2026-05-14T19:42:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690190</loc>
  <lastmod>2026-05-14T19:42:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み付きマルチセットオートマトンと正規表現のアルゴリズムと学習（Algorithms and Training for Weighted Multiset Automata and Regular Expressions）</news:title>
   <news:publication_date>2026-05-14T19:42:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690188</loc>
  <lastmod>2026-05-14T19:41:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的サンプルを想定したメタラーニングの実践（Adversarial Meta-Learning）</news:title>
   <news:publication_date>2026-05-14T19:41:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690186</loc>
  <lastmod>2026-05-14T19:41:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Slalom: 信頼できるハードウェア上での高速・検証可能・プライベートなニューラルネットワーク実行（SLALOM: FAST, VERIFIABLE AND PRIVATE EXECUTION OF NEURAL NETWORKS IN TRUSTED HARDWARE）</news:title>
   <news:publication_date>2026-05-14T19:41:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690184</loc>
  <lastmod>2026-05-14T18:50:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>順序情報で次元の呪いを逃れる回帰（Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information）</news:title>
   <news:publication_date>2026-05-14T18:50:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690182</loc>
  <lastmod>2026-05-14T18:50:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Pricing Engine: 実務データで因果推定を組み込むための実装（Pricing Engine: Estimating Causal Impacts in Real World Business Settings）</news:title>
   <news:publication_date>2026-05-14T18:50:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690180</loc>
  <lastmod>2026-05-14T18:50:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビッグデータからのデータラーニング（Data learning from big data）</news:title>
   <news:publication_date>2026-05-14T18:50:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690178</loc>
  <lastmod>2026-05-14T18:49:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Badger: フィジングとシンボリック実行を組み合わせた複雑性解析（Badger: Complexity Analysis with Fuzzing and Symbolic Execution）</news:title>
   <news:publication_date>2026-05-14T18:49:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690176</loc>
  <lastmod>2026-05-14T18:48:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布ベース均衡とRBF分類器によるソフトウェア欠陥予測の最適化（DBBRBF - Convalesce optimization for software defect prediction problem using hybrid distribution base balance instance selection and radial basis Function classifier）</news:title>
   <news:publication_date>2026-05-14T18:48:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690174</loc>
  <lastmod>2026-05-14T18:48:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話型レコメンダーシステムの統合的提案（Conversational Recommender System）</news:title>
   <news:publication_date>2026-05-14T18:48:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690172</loc>
  <lastmod>2026-05-14T18:48:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗闇の正義：暗号化された敏感属性による公平性（Blind Justice: Fairness with Encrypted Sensitive Attributes）</news:title>
   <news:publication_date>2026-05-14T18:48:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690170</loc>
  <lastmod>2026-05-14T17:56:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>掘削ビットでの岩石種識別を実現するデータ駆動モデル（Data-driven model for the identification of the rock type at a drilling bit）</news:title>
   <news:publication_date>2026-05-14T17:56:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690168</loc>
  <lastmod>2026-05-14T17:56:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全自動断面検出による撮像ビュー計画の革新（Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents）</news:title>
   <news:publication_date>2026-05-14T17:56:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690166</loc>
  <lastmod>2026-05-14T17:56:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長さ正規化を組み込んだエンドツーエンド話者認証の解析（Analysis of Length Normalization in End-to-End Speaker Verification System）</news:title>
   <news:publication_date>2026-05-14T17:56:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690164</loc>
  <lastmod>2026-05-14T17:55:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>整数潜在変数モデルにおける学習と入れ子自動微分（Learning in Integer Latent Variable Models with Nested Automatic Differentiation）</news:title>
   <news:publication_date>2026-05-14T17:55:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690162</loc>
  <lastmod>2026-05-14T17:55:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>よく調整されたラッソ（The Well Tempered Lasso）</news:title>
   <news:publication_date>2026-05-14T17:55:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690160</loc>
  <lastmod>2026-05-14T17:54:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wave-U-Netによる時間領域エンドツーエンド音源分離（WAVE-U-NET: A MULTI-SCALE NEURAL NETWORK FOR END-TO-END AUDIO SOURCE SEPARATION）</news:title>
   <news:publication_date>2026-05-14T17:54:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690158</loc>
  <lastmod>2026-05-14T17:54:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データを量子化に合わせる発想の転換（Spreading Vectors for Similarity Search）</news:title>
   <news:publication_date>2026-05-14T17:54:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690156</loc>
  <lastmod>2026-05-14T17:03:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多言語感情分析：少量データ向けRNNフレームワーク（Multilingual Sentiment Analysis: An RNN-Based Framework for Limited Data）</news:title>
   <news:publication_date>2026-05-14T17:03:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690154</loc>
  <lastmod>2026-05-14T17:03:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CBRに基づくBAM切替えの類似度関数評価（Evaluating CBR Similarity Functions for BAM Switching in Networks with Dynamic Traffic Profile）</news:title>
   <news:publication_date>2026-05-14T17:03:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690152</loc>
  <lastmod>2026-05-14T17:02:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理制約付き逆解析による土壌水分と植生水分の高解像度取得（A Physically Constrained Inversion for Super-resolved Passive Microwave Retrieval of Soil Moisture and Vegetation Water Content in L-band）</news:title>
   <news:publication_date>2026-05-14T17:02:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690150</loc>
  <lastmod>2026-05-14T17:01:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フィデリティに基づく確率的Q学習による量子システム制御（Fidelity-based Probabilistic Q-learning for Control of Quantum Systems）</news:title>
   <news:publication_date>2026-05-14T17:01:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690148</loc>
  <lastmod>2026-05-14T17:01:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジ更新を伴うニューラルメッセージパッシングによる分子・材料の性質予測（Neural Message Passing with Edge Updates for Predicting Properties of Molecules and Materials）</news:title>
   <news:publication_date>2026-05-14T17:01:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690146</loc>
  <lastmod>2026-05-14T17:01:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子システムの推定とロバスト制御に関する最近の進展（Several recent developments in estimation and robust control of quantum systems）</news:title>
   <news:publication_date>2026-05-14T17:01:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690144</loc>
  <lastmod>2026-05-14T17:00:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックボックスFDRの実用化（Black Box FDR）</news:title>
   <news:publication_date>2026-05-14T17:00:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690142</loc>
  <lastmod>2026-05-14T16:10:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層型GANによる具現化された自己認識モデルの学習（HIERARCHY OF GANS FOR LEARNING EMBODIED SELF-AWARENESS MODEL）</news:title>
   <news:publication_date>2026-05-14T16:10:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690140</loc>
  <lastmod>2026-05-14T16:09:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習によるCICY三次元多様体の解析（Machine Learning CICY Threefolds）</news:title>
   <news:publication_date>2026-05-14T16:09:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690138</loc>
  <lastmod>2026-05-14T16:09:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語サブスペースによるテキスト分類（Text Classification based on Word Subspace with Term-Frequency）</news:title>
   <news:publication_date>2026-05-14T16:09:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690136</loc>
  <lastmod>2026-05-14T16:08:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間差分変分オートエンコーダ（Temporal Difference Variational Auto-Encoder）</news:title>
   <news:publication_date>2026-05-14T16:08:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690134</loc>
  <lastmod>2026-05-14T16:08:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stein変分ニュートン法（A Stein variational Newton method）</news:title>
   <news:publication_date>2026-05-14T16:08:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690132</loc>
  <lastmod>2026-05-14T16:08:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確かさを利用したサニティチェックによる術後脳腫瘍腔セグメンテーション（Uncertainty-driven Sanity Check: Application to Postoperative Brain Tumor Cavity Segmentation）</news:title>
   <news:publication_date>2026-05-14T16:08:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690130</loc>
  <lastmod>2026-05-14T16:07:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回転対称性を活かした病理画像向け畳み込みニューラルネットワーク（Rotation Equivariant CNNs for Digital Pathology）</news:title>
   <news:publication_date>2026-05-14T16:07:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690128</loc>
  <lastmod>2026-05-14T15:16:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人物認識における同定と文脈学習の統合（Unifying Identification and Context Learning for Person Recognition）</news:title>
   <news:publication_date>2026-05-14T15:16:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690126</loc>
  <lastmod>2026-05-14T15:16:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディップル図における深非弾的散乱のNLO軟グルーオン発散の因数分解（Factorization of the soft gluon divergence from the dipole picture deep inelastic scattering cross sections at next-to-leading order）</news:title>
   <news:publication_date>2026-05-14T15:16:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690124</loc>
  <lastmod>2026-05-14T15:15:47Z</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おける深層マルチスケール構造（DEEP MULTI-SCALE ARCHITECTURES FOR MONOCULAR DEPTH ESTIMATION）</news:title>
   <news:publication_date>2026-05-14T15:15:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690122</loc>
  <lastmod>2026-05-14T15:15:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D FCN特徴駆動回帰フォレストによる膵臓局在化とセグメンテーション（3D FCN Feature Driven Regression Forest-Based Pancreas Localization and Segmentation）</news:title>
   <news:publication_date>2026-05-14T15:15:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690120</loc>
  <lastmod>2026-05-14T15:14:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ID対スポット顔認証における大規模二枚学習（Large-scale Bisample Learning on ID Versus Spot Face Recognition）</news:title>
   <news:publication_date>2026-05-14T15:14:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690118</loc>
  <lastmod>2026-05-14T15:14:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>道路上の車種・型式識別に向けた教師なし特徴学習（Unsupervised Feature Learning Toward a Real-time Vehicle Make and Model Recognition）</news:title>
   <news:publication_date>2026-05-14T15:14:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690116</loc>
  <lastmod>2026-05-14T15:13:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>新生児けいれん検出における深い全畳み込みネットワークの適用（A Fully Convolutional Architecture for Neonatal Seizure Detection）</news:title>
   <news:publication_date>2026-05-14T15:13:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
</urlset>
