<?xml version="1.0" encoding="UTF-8"?>
<!--generator='jetpack-15.8-a.7'-->
<!--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/684633</loc>
  <lastmod>2026-04-29T05:29:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模MIMOにおけるチャネル推定とユーザ群分けの同時処理（Joint Channel Estimation and User Grouping for Massive MIMO Systems）</news:title>
   <news:publication_date>2026-04-29T05:29:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684631</loc>
  <lastmod>2026-04-29T05:22:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習に基づく音響モデルの近年の進展（Recent Progresses in Deep Learning based Acoustic Models）</news:title>
   <news:publication_date>2026-04-29T05:22:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684629</loc>
  <lastmod>2026-04-29T05:22:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱ラベル学習による音声イベント検出の再考（A Closer Look at Weak Label Learning for Audio Events）</news:title>
   <news:publication_date>2026-04-29T05:22:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684627</loc>
  <lastmod>2026-04-29T05:22:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乱流制御のためのLSTMによる低次元モデル構築（A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks）</news:title>
   <news:publication_date>2026-04-29T05:22:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684625</loc>
  <lastmod>2026-04-29T05:21:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3Dセグメント記述子を学習して場所認識を行う（Learning 3D Segment Descriptors for Place Recognition）</news:title>
   <news:publication_date>2026-04-29T05:21:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684623</loc>
  <lastmod>2026-04-29T05:21:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光と物質の超強結合の最前線（Ultrastrong coupling regimes of light-matter interaction）</news:title>
   <news:publication_date>2026-04-29T05:21:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684621</loc>
  <lastmod>2026-04-29T05:19:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットの「黒箱」をひらく：stop/top識別の事例研究（Opening the black box of neural nets: case studies in stop/top discrimination）</news:title>
   <news:publication_date>2026-04-29T05:19:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684619</loc>
  <lastmod>2026-04-29T04:24:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宣言的に定義されたエントロピー制約による半教師あり学習（Semi-Supervised Learning with Declaratively Specified Entropy Constraints）</news:title>
   <news:publication_date>2026-04-29T04:24:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684617</loc>
  <lastmod>2026-04-29T04:24:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>常識知識の発掘は知識ベース補完か？新規性の影響に関する研究（Commonsense mining as knowledge base completion? A study on the impact of novelty）</news:title>
   <news:publication_date>2026-04-29T04:24:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684615</loc>
  <lastmod>2026-04-29T04:21:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepTriangleによる保険支払準備金の予測革新（DeepTriangle: A Deep Learning Approach to Loss Reserving）</news:title>
   <news:publication_date>2026-04-29T04:21:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684613</loc>
  <lastmod>2026-04-29T04:19:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク細粒度が転移学習にもたらす効果（On the Effectiveness of Task Granularity for Transfer Learning）</news:title>
   <news:publication_date>2026-04-29T04:19:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684611</loc>
  <lastmod>2026-04-29T04:18:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>産業界への対話型探索ベースソフトウェアテストの移転（Transferring Interactive Search-Based Software Testing to Industry）</news:title>
   <news:publication_date>2026-04-29T04:18:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684609</loc>
  <lastmod>2026-04-29T04:18:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡ネットワーク表現学習の新手法と実務への示唆（ImVerde: Vertex-Diminished Random Walk for Learning Imbalanced Network Representation）</news:title>
   <news:publication_date>2026-04-29T04:18:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684607</loc>
  <lastmod>2026-04-29T04:18:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース符号化によるイベント駆動型カメラの時系列学習（A Sparse Coding Multi-Scale Precise-Timing Machine Learning Algorithm for Neuromorphic Event-Based Sensors）</news:title>
   <news:publication_date>2026-04-29T04:18:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684605</loc>
  <lastmod>2026-04-29T03:21:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠測サンプルから学ぶスパース辞書学習（On Learning Sparsely Used Dictionaries from Incomplete Samples）</news:title>
   <news:publication_date>2026-04-29T03:21:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684603</loc>
  <lastmod>2026-04-29T03:20:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パッチベースCNNによるボーカル旋律抽出（VOCAL MELODY EXTRACTION USING PATCH-BASED CNN）</news:title>
   <news:publication_date>2026-04-29T03:20:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684601</loc>
  <lastmod>2026-04-29T03:18:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マウス臓器の自動セグメンテーション（Automated Mouse Organ Segmentation: A Deep Learning Based Solution）</news:title>
   <news:publication_date>2026-04-29T03:18:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684599</loc>
  <lastmod>2026-04-29T03:15:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アベール1758における二重ラジオハローの発見（LOFAR discovery of a double radio halo system in Abell 1758）</news:title>
   <news:publication_date>2026-04-29T03:15:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684597</loc>
  <lastmod>2026-04-29T03:15:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>評価指標の罠を乗り越える報酬学習——視覚ストーリーテリングにおける敵対的報酬学習（Adversarial Reward Learning for Visual Storytelling）</news:title>
   <news:publication_date>2026-04-29T03:15:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684595</loc>
  <lastmod>2026-04-29T03:15:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANを使ったDOOMレベル生成の可能性（DOOM Level Generation using Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-04-29T03:15:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684593</loc>
  <lastmod>2026-04-29T03:14:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>現実的な半教師あり学習の評価法（Realistic Evaluation of Deep Semi-Supervised Learning Algorithms）</news:title>
   <news:publication_date>2026-04-29T03:14:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684591</loc>
  <lastmod>2026-04-29T02:19:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医学文献における有害事象検出の自動化（Automated Detection of Adverse Drug Reactions in the Biomedical Literature Using Convolutional Neural Networks and Biomedical Word Embeddings）</news:title>
   <news:publication_date>2026-04-29T02:19:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684589</loc>
  <lastmod>2026-04-29T02:18:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>殻越えを超えた構造形成（Structure formation beyond shell-crossing: nonperturbative expansions and late-time attractors）</news:title>
   <news:publication_date>2026-04-29T02:18:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684587</loc>
  <lastmod>2026-04-29T02:17:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模イベント埋め込みと再帰型ネットワークによるネイティブ広告CTR予測の改善（Improving Native Ads CTR Prediction by Large Scale Event Embedding and Recurrent Networks）</news:title>
   <news:publication_date>2026-04-29T02:17:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684585</loc>
  <lastmod>2026-04-29T02:16:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子版生成的敵対ネットワークの提案（Quantum generative adversarial learning）</news:title>
   <news:publication_date>2026-04-29T02:16:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684583</loc>
  <lastmod>2026-04-29T02:10:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PULP‑HD：低消費電力並列プラットフォーム上での高次元計算の加速（PULP‑HD: Accelerating Brain‑Inspired High‑Dimensional Computing on a Parallel Ultra‑Low Power Platform）</news:title>
   <news:publication_date>2026-04-29T02:10:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684581</loc>
  <lastmod>2026-04-29T02:09:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>現実と合わない深度認識を埋める手法（Keep it Unreal: Bridging the Realism Gap for 2.5D Recognition with Geometry Priors Only）</news:title>
   <news:publication_date>2026-04-29T02:09:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684579</loc>
  <lastmod>2026-04-29T02:08:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Seer: 大規模トレースデータでクラウドデバッグの複雑さを切り拓く（Seer: Leveraging Big Data to Navigate The Increasing Complexity of Cloud Debugging）</news:title>
   <news:publication_date>2026-04-29T02:08:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684577</loc>
  <lastmod>2026-04-29T01:14:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WordNetに視覚的類似度を導入する試み（A Visual Distance for WordNet）</news:title>
   <news:publication_date>2026-04-29T01:14:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684575</loc>
  <lastmod>2026-04-29T01:14:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ないラベルで偽情報を見抜く半教師ありテンソル埋め込み法（Semi-supervised Content-based Detection of Misinformation via Tensor Embeddings）</news:title>
   <news:publication_date>2026-04-29T01:14:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684573</loc>
  <lastmod>2026-04-29T01:14:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胎児頭部バイオメトリクスの自動化で人間レベルを達成する手法（Human-level Performance On Automatic Head Biometrics In Fetal Ultrasound Using Fully Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-04-29T01:14:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684571</loc>
  <lastmod>2026-04-29T01:12:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>過渡的理想係数で読み解くペロブスカイト太陽電池の再結合機構（Identifying dominant recombination mechanisms in perovskite solar cells by measuring the transient ideality factor）</news:title>
   <news:publication_date>2026-04-29T01:12:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684569</loc>
  <lastmod>2026-04-29T01:12:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習の情報理論的考察（An Information-Theoretic View for Deep Learning）</news:title>
   <news:publication_date>2026-04-29T01:12:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684567</loc>
  <lastmod>2026-04-29T01:12:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な多目的ニューラルアーキテクチャ探索におけるラマルキアン進化（Efficient Multi-Objective Neural Architecture Search via Lamarckian Evolution）</news:title>
   <news:publication_date>2026-04-29T01:12:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684565</loc>
  <lastmod>2026-04-29T01:12:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>北極域の磁場トポロジー（Magnetic topology of the north solar pole）</news:title>
   <news:publication_date>2026-04-29T01:12:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684563</loc>
  <lastmod>2026-04-29T00:20:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベル認識型二重転移学習による診療科横断の医療固有表現抽出（Label-aware Double Transfer Learning for Cross-Specialty Medical Named Entity Recognition）</news:title>
   <news:publication_date>2026-04-29T00:20:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684561</loc>
  <lastmod>2026-04-29T00:14:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VNIRハイパースペクトルによる土壌水分推定の機械学習フレームワークの構築 (Developing a Machine Learning Framework for Estimating Soil Moisture with VNIR Hyperspectral Data)</news:title>
   <news:publication_date>2026-04-29T00:14:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684559</loc>
  <lastmod>2026-04-29T00:13:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的条件付き勾配法：凸最小化から準モジュラ最大化へ（Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization）</news:title>
   <news:publication_date>2026-04-29T00:13:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684557</loc>
  <lastmod>2026-04-29T00:12:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>既存アプリケーションと深層ニューラルネットワークの統合手法：Estimate and Replace（Estimate and Replace: A Novel Approach to Integrating Deep Neural Networks with Existing Applications）</news:title>
   <news:publication_date>2026-04-29T00:12:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684555</loc>
  <lastmod>2026-04-29T00:12:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートフォン向け隠れマルコフモデルと識別的アンサンブル学習による部屋認識（Room Recognition Using Discriminative Ensemble Learning with Hidden Markov Models for Smartphones）</news:title>
   <news:publication_date>2026-04-29T00:12:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684553</loc>
  <lastmod>2026-04-29T00:11:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スキルミオン結晶モデルによる核物質の磁場効果（Magnetic field effect on nuclear matter from skyrmion crystal model）</news:title>
   <news:publication_date>2026-04-29T00:11:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684551</loc>
  <lastmod>2026-04-29T00:11:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>あらゆるモノの認証を環境で補強する（Authentication of Everything in the Internet of Things: Learning and Environmental Effects）</news:title>
   <news:publication_date>2026-04-29T00:11:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684549</loc>
  <lastmod>2026-04-28T23:18:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バックトランスレーションによる文体転換（Style Transfer Through Back-Translation）</news:title>
   <news:publication_date>2026-04-28T23:18:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684547</loc>
  <lastmod>2026-04-28T23:18:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般集合と測度に対する率-歪み理論（Rate-Distortion Theory for General Sets and Measures）</news:title>
   <news:publication_date>2026-04-28T23:18:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684545</loc>
  <lastmod>2026-04-28T23:18:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>基本および多層Echo State Network再帰オートエンコーダの起源（Genesis of Basic and Multi-Layer Echo State Network Recurrent Autoencoder for Efficient Data Representations）</news:title>
   <news:publication_date>2026-04-28T23:18:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684543</loc>
  <lastmod>2026-04-28T23:16:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発射管制の音声認識を劇的に改善する手法（Automatic speech recognition for launch control center communication using recurrent neural networks with data augmentation and custom language model）</news:title>
   <news:publication_date>2026-04-28T23:16:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684541</loc>
  <lastmod>2026-04-28T23:16:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボット操作空間を高速に推定する深層サブスペース学習（Deep Neural Network Based Subspace Learning of Robotic Manipulator Workspace Mapping）</news:title>
   <news:publication_date>2026-04-28T23:16:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684539</loc>
  <lastmod>2026-04-28T23:16:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相関フィルタにおける識別性と信頼性の同時学習（Correlation Tracking via Joint Discrimination and Reliability Learning）</news:title>
   <news:publication_date>2026-04-28T23:16:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684537</loc>
  <lastmod>2026-04-28T23:15:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケッチで顔を直感的に編集する技術（FaceShop: Deep Sketch-based Face Image Editing）</news:title>
   <news:publication_date>2026-04-28T23:15:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684535</loc>
  <lastmod>2026-04-28T22:23:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の確率遷移下での平均報酬最適化とω-正規制約（Learning-Based Mean-Payoff Optimization in an Unknown MDP under Omega-Regular Constraints）</news:title>
   <news:publication_date>2026-04-28T22:23:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684533</loc>
  <lastmod>2026-04-28T22:14:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fortranから使える粒子シミュレーション基盤の橋渡し（Fortran Interface to FDPS）</news:title>
   <news:publication_date>2026-04-28T22:14:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684531</loc>
  <lastmod>2026-04-28T22:14:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アウトライヤー分類と自己符号化器による境界層プラズマ解析（Outlier classification using Autoencoders: application for fluctuation driven flows in fusion plasmas）</news:title>
   <news:publication_date>2026-04-28T22:14:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684529</loc>
  <lastmod>2026-04-28T22:11:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>論理断片の被覆と分離におけるモジュラ述語の役割（COVERING AND SEPARATION FOR LOGICAL FRAGMENTS WITH MODULAR PREDICATES）</news:title>
   <news:publication_date>2026-04-28T22:11:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684527</loc>
  <lastmod>2026-04-28T22:11:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>道路表面分類に対する深層畳み込みニューラルネットワークの評価 (Assessment of Deep Convolutional Neural Networks for Road Surface Classification)</news:title>
   <news:publication_date>2026-04-28T22:11:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684525</loc>
  <lastmod>2026-04-28T22:11:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インストール試行によるソフトウェア制約の学習（Learning Software Constraints via Installation Attempts）</news:title>
   <news:publication_date>2026-04-28T22:11:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684523</loc>
  <lastmod>2026-04-28T22:11:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習スケジュールによるマルチタスク学習（Scheduled Multi-Task Learning: From Syntax to Translation）</news:title>
   <news:publication_date>2026-04-28T22:11:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684521</loc>
  <lastmod>2026-04-28T21:19:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D点群データから動的ジェスチャを時空間学習する手法（Spatiotemporal Learning of Dynamic Gestures from 3D Point Cloud Data）</news:title>
   <news:publication_date>2026-04-28T21:19:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684519</loc>
  <lastmod>2026-04-28T21:11:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同心円上の表現で差をつける：Homocentric HypersphereによるPerson ReIDの新視点（Homocentric Hypersphere Feature Embedding for Person Re-identification）</news:title>
   <news:publication_date>2026-04-28T21:11:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684517</loc>
  <lastmod>2026-04-28T21:10:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>見えない部分を学ぶ技術：End-to-Endで学習可能なアモーダルインスタンス分割（Learning to See the Invisible: End-to-End Trainable Amodal Instance Segmentation）</news:title>
   <news:publication_date>2026-04-28T21:10:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684515</loc>
  <lastmod>2026-04-28T21:10:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程のための合成推論（Composite Inference for Gaussian Processes）</news:title>
   <news:publication_date>2026-04-28T21:10:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684513</loc>
  <lastmod>2026-04-28T21:09:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ALMAによるSSA22深宇宙探索：1.1mmで描く20平方分の探査（ALMA Deep Field in SSA22: Survey Design and Source Catalog of a 20 arcmin2 Survey at 1.1 mm）</news:title>
   <news:publication_date>2026-04-28T21:09:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684511</loc>
  <lastmod>2026-04-28T21:09:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乗算的特徴量で強化する単語関係判定（Integrating Multiplicative Features into Supervised Distributional Methods for Lexical Entailment）</news:title>
   <news:publication_date>2026-04-28T21:09:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684509</loc>
  <lastmod>2026-04-28T21:09:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepEmoによる感情表現の強化と自動抽出（DeepEmo: Learning and Enriching Pattern-Based Emotion Representations）</news:title>
   <news:publication_date>2026-04-28T21:09:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684507</loc>
  <lastmod>2026-04-28T20:17:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>H2輝線で捉えた惑星状星雲の拡張構造（Extended Structures of Planetary Nebulae Detected in H2 Emission）</news:title>
   <news:publication_date>2026-04-28T20:17:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684505</loc>
  <lastmod>2026-04-28T20:17:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハードとソフトのしきい値のあいだ：最適反復しきい値アルゴリズム（Between hard and soft thresholding: optimal iterative thresholding algorithms）</news:title>
   <news:publication_date>2026-04-28T20:17:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684503</loc>
  <lastmod>2026-04-28T20:15:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>目的関数の内在次元を測る（MEASURING THE INTRINSIC DIMENSION OF OBJECTIVE LANDSCAPES）</news:title>
   <news:publication_date>2026-04-28T20:15:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684501</loc>
  <lastmod>2026-04-28T20:15:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク指向のテキスト含意を深掘りする手法（End-Task Oriented Textual Entailment via Deep Explorations of Inter-Sentence Interactions）</news:title>
   <news:publication_date>2026-04-28T20:15:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684499</loc>
  <lastmod>2026-04-28T20:15:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非定常ストリームからのマニフォールド学習（Learning Manifolds from Non-stationary Streams）</news:title>
   <news:publication_date>2026-04-28T20:15:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684497</loc>
  <lastmod>2026-04-28T20:15:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化SUMCOR多視点正準相関解析による大規模データ処理（Structured SUMCOR Multiview Canonical Correlation Analysis for Large-Scale Data）</news:title>
   <news:publication_date>2026-04-28T20:15:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684495</loc>
  <lastmod>2026-04-28T20:14:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>P波到達時刻と初動極性を深層学習で自動化する（P-wave arrival picking and first-motion polarity determination with deep learning）</news:title>
   <news:publication_date>2026-04-28T20:14:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684493</loc>
  <lastmod>2026-04-28T19:22:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話音声における教師なし同期距離（Towards an Unsupervised Entrainment Distance in Conversational Speech using Deep Neural Networks）</news:title>
   <news:publication_date>2026-04-28T19:22:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684491</loc>
  <lastmod>2026-04-28T19:22:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列グラフ列に対するブロック構造ベースモデル（Block-Structure Based Time-Series Models For Graph Sequences）</news:title>
   <news:publication_date>2026-04-28T19:22:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684489</loc>
  <lastmod>2026-04-28T19:22:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アウト・オブ・ディストリビューション学習で堅牢化するCNN（Towards Dependable Deep Convolutional Neural Networks with Out-distribution Learning）</news:title>
   <news:publication_date>2026-04-28T19:22:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684487</loc>
  <lastmod>2026-04-28T19:21:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>API呼び出し列に対するクエリ効率の高いブラックボックス攻撃（Query-Efficient Black-Box Attack Against Sequence-Based Malware Classifiers）</news:title>
   <news:publication_date>2026-04-28T19:21:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684485</loc>
  <lastmod>2026-04-28T19:21:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neural-Brane: 属性付きネットワーク埋め込みの新潮流（Neural-Brane: Neural Bayesian Personalized Ranking for Attributed Network Embedding）</news:title>
   <news:publication_date>2026-04-28T19:21:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684483</loc>
  <lastmod>2026-04-28T19:21:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッド車のリアルタイム確率的予測制御によるエネルギー管理（Real-Time Stochastic Predictive Control for Hybrid Vehicle Energy Management）</news:title>
   <news:publication_date>2026-04-28T19:21:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684481</loc>
  <lastmod>2026-04-28T19:21:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>翻訳されている中国語の統語的特徴の検出 (Detecting Syntactic Features of Translated Chinese)</news:title>
   <news:publication_date>2026-04-28T19:21:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684479</loc>
  <lastmod>2026-04-28T18:29:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教室での本格的研究体験（Authentic Research in the Classroom for Teachers and Students）</news:title>
   <news:publication_date>2026-04-28T18:29:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684477</loc>
  <lastmod>2026-04-28T18:28:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教育者と研究者を結ぶNITARPの13年の教訓（The NASA/IPAC Teacher Archive Research Program (NITARP))</news:title>
   <news:publication_date>2026-04-28T18:28:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684475</loc>
  <lastmod>2026-04-28T18:28:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>睡眠脳に現れる周期的交互パターンを機械学習で識別する試み（A machine learning model for identifying cyclic alternating patterns in the sleeping brain）</news:title>
   <news:publication_date>2026-04-28T18:28:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684473</loc>
  <lastmod>2026-04-28T18:28:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>工作物を使った代替現実ゲーム型ワークショップの設計（&amp;quot;It was Colonel Mustard in the Study with the Candlestick&amp;quot;: Using Artifacts to Create An Alternate Reality Game–The Unworkshop）</news:title>
   <news:publication_date>2026-04-28T18:28:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684471</loc>
  <lastmod>2026-04-28T18:27:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚特徴を活用したスタイルトレンド発見（Discovering Style Trends through Deep Visually Aware Latent Item Embeddings）</news:title>
   <news:publication_date>2026-04-28T18:27:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684469</loc>
  <lastmod>2026-04-28T18:27:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>StreamBEDによる市民科学者の現場感覚訓練（StreamBED: Training Citizen Scientists to Make Qualitative Judgments Using Embodied Virtual Reality Training）</news:title>
   <news:publication_date>2026-04-28T18:27:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684467</loc>
  <lastmod>2026-04-28T18:27:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非一様ジオメトリにおける同時ショット反演と高速データ補間（Simultaneous shot inversion for nonuniform geometries using fast data interpolation）</news:title>
   <news:publication_date>2026-04-28T18:27:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684465</loc>
  <lastmod>2026-04-28T17:35:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Rogueのダンジョン探索を分割A3Cで解く（Crawling in Rogue’s dungeons with (partitioned) A3C）</news:title>
   <news:publication_date>2026-04-28T17:35:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684463</loc>
  <lastmod>2026-04-28T17:35:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepDIVA: 再現可能な実験を素早く組めるPythonフレームワーク（DeepDIVA: A Highly-Functional Python Framework for Reproducible Experiments）</news:title>
   <news:publication_date>2026-04-28T17:35:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684461</loc>
  <lastmod>2026-04-28T17:34:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ボルツマン符号化敵対生成機（Boltzmann Encoded Adversarial Machines）</news:title>
   <news:publication_date>2026-04-28T17:34:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684459</loc>
  <lastmod>2026-04-28T17:33:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>科学的結果の頑健性を保証する統計的推論の理論（A Theory of Statistical Inference for Ensuring the Robustness of Scientific Results）</news:title>
   <news:publication_date>2026-04-28T17:33:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684457</loc>
  <lastmod>2026-04-28T17:33:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型の調査報道と腐敗検出（Data-Driven Investigative Journalism For Connectas Dataset）</news:title>
   <news:publication_date>2026-04-28T17:33:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684455</loc>
  <lastmod>2026-04-28T17:32:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>腕のジェスチャーで群ロボットを操る解釈子の設計（Gesture based Human-Swarm Interactions for Formation Control using interpreters）</news:title>
   <news:publication_date>2026-04-28T17:32:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684453</loc>
  <lastmod>2026-04-28T17:32:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低密度環境におけるフロック形成の誘導（Influencing Flock Formation in Low-Density Settings）</news:title>
   <news:publication_date>2026-04-28T17:32:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684451</loc>
  <lastmod>2026-04-28T16:40:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>新しい天の川衛星の詳細な観測（A Deeper Look at the New Milky Way Satellites）</news:title>
   <news:publication_date>2026-04-28T16:40:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684449</loc>
  <lastmod>2026-04-28T16:40:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子版生成的敵対ネットワークの提案（Quantum generative adversarial networks）</news:title>
   <news:publication_date>2026-04-28T16:40:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684447</loc>
  <lastmod>2026-04-28T16:39:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Projective Simulationをナビゲーション問題で評価する（Benchmarking projective simulation in navigation problems）</news:title>
   <news:publication_date>2026-04-28T16:39:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684445</loc>
  <lastmod>2026-04-28T16:38:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>常識を備えた記号強化学習（Towards Symbolic Reinforcement Learning with Common Sense）</news:title>
   <news:publication_date>2026-04-28T16:38:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684443</loc>
  <lastmod>2026-04-28T16:38:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゼロショット視覚模倣（ZERO-SHOT VISUAL IMITATION）</news:title>
   <news:publication_date>2026-04-28T16:38:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684441</loc>
  <lastmod>2026-04-28T16:38:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限られたクエリと情報で行うブラックボックス敵対的攻撃（Black-box Adversarial Attacks with Limited Queries and Information）</news:title>
   <news:publication_date>2026-04-28T16:38:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684439</loc>
  <lastmod>2026-04-28T16:38:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>任意のサポートを持つまばら辞書学習への接近（Towards Learning Sparsely Used Dictionaries with Arbitrary Supports）</news:title>
   <news:publication_date>2026-04-28T16:38:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684437</loc>
  <lastmod>2026-04-28T15:45:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模なシーン文字検証とGuided Attention（Large Scale Scene Text Verification with Guided Attention）</news:title>
   <news:publication_date>2026-04-28T15:45:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684435</loc>
  <lastmod>2026-04-28T15:45:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低温・金触媒によるグラフェンエッチングと水蒸気の役割（On the Role of Water Vapor and Process Gasses in Low-Temperature Gold-Catalyzed Graphene Etching）</news:title>
   <news:publication_date>2026-04-28T15:45:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684433</loc>
  <lastmod>2026-04-28T15:44:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軽量で頭部姿勢に不変な注視追跡（Light-weight Head Pose Invariant Gaze Tracking）</news:title>
   <news:publication_date>2026-04-28T15:44:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684431</loc>
  <lastmod>2026-04-28T15:43:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベクトル化による敵対的事例への防御（VectorDefense: Vectorization as a Defense to Adversarial Examples）</news:title>
   <news:publication_date>2026-04-28T15:43:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684429</loc>
  <lastmod>2026-04-28T15:43:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な機械学習で隠れたスピン秩序を探る（Probing hidden spin order with interpretable machine learning）</news:title>
   <news:publication_date>2026-04-28T15:43:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684427</loc>
  <lastmod>2026-04-28T15:42:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間ニューラルネットワークによる系列予測と関係性発見（Spatio-Temporal Neural Networks for Space-Time Series Forecasting and Relations Discovery）</news:title>
   <news:publication_date>2026-04-28T15:42:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684425</loc>
  <lastmod>2026-04-28T15:42:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複合凸最小化の条件付き勾配フレームワーク（A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming）</news:title>
   <news:publication_date>2026-04-28T15:42:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684423</loc>
  <lastmod>2026-04-28T14:51:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チャンネル強化型畳み込みニューラルネットワークと転移学習（A New Channel Boosted Convolutional Neural Network using Transfer Learning）</news:title>
   <news:publication_date>2026-04-28T14:51:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684421</loc>
  <lastmod>2026-04-28T14:50:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全歩行サイクルからの個人識別（Person Identification from Partial Gait Cycle Using Fully Convolutional Neural Network）</news:title>
   <news:publication_date>2026-04-28T14:50:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684419</loc>
  <lastmod>2026-04-28T14:50:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元推定と適応的マルチファクターモデル（High-Dimensional Estimation, Basis Assets, and the Adaptive Multi-Factor Model）</news:title>
   <news:publication_date>2026-04-28T14:50:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684417</loc>
  <lastmod>2026-04-28T14:49:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dropping Networksによる転移学習の新展開（Dropping Networks For Transfer Learning）</news:title>
   <news:publication_date>2026-04-28T14:49:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684415</loc>
  <lastmod>2026-04-28T14:49:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同時手番ゲームにおけるMC-MCTS選択の検証と示唆（Analysis of Hannan Consistent Selection for Monte Carlo Tree Search in Simultaneous Move Games）</news:title>
   <news:publication_date>2026-04-28T14:49:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684413</loc>
  <lastmod>2026-04-28T14:48:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分形状に頑健な整列を実現するALIGNet（ALIGNet: Partial-Shape Agnostic Alignment via Unsupervised Learning）</news:title>
   <news:publication_date>2026-04-28T14:48:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684411</loc>
  <lastmod>2026-04-28T14:48:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像から詩を生成する技術（Beyond Narrative Description: Generating Poetry from Images by Multi-Adversarial Training）</news:title>
   <news:publication_date>2026-04-28T14:48:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684409</loc>
  <lastmod>2026-04-28T13:57:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドローン操作をカードで組む仕組み（CardKit: A Card-Based Programming Framework for Drones）</news:title>
   <news:publication_date>2026-04-28T13:57:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684407</loc>
  <lastmod>2026-04-28T13:56:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚と言語を注意機構で結びつけるナビゲーション学習（Attention Based Natural Language Grounding by Navigating Virtual Environment）</news:title>
   <news:publication_date>2026-04-28T13:56:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684405</loc>
  <lastmod>2026-04-28T13:56:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デコレートされたバッチ正規化（Decorrelated Batch Normalization）</news:title>
   <news:publication_date>2026-04-28T13:56:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684403</loc>
  <lastmod>2026-04-28T13:55:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートモビリティを支える経路計画にGANを使う意義（Path Planning in Support of Smart Mobility Applications using Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-04-28T13:55:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684401</loc>
  <lastmod>2026-04-28T13:54:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>状態分布を考慮したサンプリングによる深層Q学習の改善（State Distribution-aware Sampling for Deep Q-learning）</news:title>
   <news:publication_date>2026-04-28T13:54:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684399</loc>
  <lastmod>2026-04-28T13:54:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VCC2018のスプーフィング指標による音声変換アーティファクト評価（A Spoofing Benchmark for the 2018 Voice Conversion Challenge: Leveraging from Spoofing Countermeasures for Speech Artifact Assessment）</news:title>
   <news:publication_date>2026-04-28T13:54:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684397</loc>
  <lastmod>2026-04-28T13:54:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>腹部多臓器セグメンテーションにおける器官注意ネットワークと統計的融合（Abdominal Multi-organ Segmentation with Organ-Attention Networks and Statistical Fusion）</news:title>
   <news:publication_date>2026-04-28T13:54:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684395</loc>
  <lastmod>2026-04-28T13:02:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間敵対ネットワークによる異常検知の新展開（STAN: Spatio-Temporal Adversarial Networks for Abnormal Event Detection）</news:title>
   <news:publication_date>2026-04-28T13:02:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684393</loc>
  <lastmod>2026-04-28T13:02:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乳癌組織像分類のための畳み込みカプセル・ネットワーク（Convolutional capsule network for classification of breast cancer histology images）</news:title>
   <news:publication_date>2026-04-28T13:02:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684391</loc>
  <lastmod>2026-04-28T13:00:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深さ優先並列処理によるニューラルネットワーク高速化（BrainSlug: Transparent Acceleration of Deep Learning Through Depth-First Parallelism）</news:title>
   <news:publication_date>2026-04-28T13:00:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684389</loc>
  <lastmod>2026-04-28T12:59:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VLocNet++：視覚位置推定とオドメトリのための深層マルチタスク学習（VLocNet++: Deep Multitask Learning for Semantic Visual Localization and Odometry）</news:title>
   <news:publication_date>2026-04-28T12:59:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684387</loc>
  <lastmod>2026-04-28T12:59:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウシアン素材合成（Gaussian Material Synthesis）</news:title>
   <news:publication_date>2026-04-28T12:59:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684385</loc>
  <lastmod>2026-04-28T12:59:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>赤外と可視画像の融合を改めて考える（DenseFuse: A Fusion Approach to Infrared and Visible Images）</news:title>
   <news:publication_date>2026-04-28T12:59:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684383</loc>
  <lastmod>2026-04-28T12:59:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>辞書学習と低ランク表現による多焦点画像融合（Multi-focus Image Fusion using dictionary learning and Low-Rank Representation）</news:title>
   <news:publication_date>2026-04-28T12:59:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684381</loc>
  <lastmod>2026-04-28T12:07:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散分布決定性方策勾配（Distributed Distributional Deterministic Policy Gradients）</news:title>
   <news:publication_date>2026-04-28T12:07:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684379</loc>
  <lastmod>2026-04-28T12:05:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散非線形シュレーディンガー方程式によるリザバーコンピューティングのモデル化（Modelling reservoir computing with the discrete nonlinear Schrödinger equation）</news:title>
   <news:publication_date>2026-04-28T12:05:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684377</loc>
  <lastmod>2026-04-28T12:05:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Facial Expression Recognitionの総覧（Deep Facial Expression Recognition: A Survey）</news:title>
   <news:publication_date>2026-04-28T12:05:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684375</loc>
  <lastmod>2026-04-28T12:04:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QANet: 局所畳み込みと全体自己注意を組み合わせたリーディング理解モデル (QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension)</news:title>
   <news:publication_date>2026-04-28T12:04:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684373</loc>
  <lastmod>2026-04-28T12:04:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率密度近似と推定のためのランダム化混合モデル（Randomized Mixture Models for Probability Density Approximation and Estimation）</news:title>
   <news:publication_date>2026-04-28T12:04:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684371</loc>
  <lastmod>2026-04-28T12:03:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表と文法を意識したSQL生成による意味解析（Semantic Parsing with Syntax- and Table-Aware SQL Generation）</news:title>
   <news:publication_date>2026-04-28T12:03:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684369</loc>
  <lastmod>2026-04-28T12:03:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異機種資源を持つモバイルエッジにおけるフェデレーテッドラーニングのクライアント選択（Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge）</news:title>
   <news:publication_date>2026-04-28T12:03:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684367</loc>
  <lastmod>2026-04-28T11:12:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視差と広帯域光学観測から導く恒星の年齢と金属量（Estimating stellar ages and metallicities from parallaxes and broadband photometry - successes and shortcomings）</news:title>
   <news:publication_date>2026-04-28T11:12:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684365</loc>
  <lastmod>2026-04-28T11:10:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多言語語彙ネットワークを使った二言語埋め込みの新手法（Bilingual Embeddings with Random Walks over Multilingual Wordnets）</news:title>
   <news:publication_date>2026-04-28T11:10:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684363</loc>
  <lastmod>2026-04-28T11:10:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク間転移の構造化と実用的意義（Taskonomy: Disentangling Task Transfer Learning）</news:title>
   <news:publication_date>2026-04-28T11:10:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684361</loc>
  <lastmod>2026-04-28T11:09:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像セグメンテーションのドメイン適応を結ぶFCAN（Fully Convolutional Adaptation Networks for Semantic Segmentation）</news:title>
   <news:publication_date>2026-04-28T11:09:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684359</loc>
  <lastmod>2026-04-28T11:09:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子構造の生物活性予測におけるSPL-Logsumによる記述子選択（QSAR Classification Modeling for Bioactivity of Molecular Structure via SPL-Logsum）</news:title>
   <news:publication_date>2026-04-28T11:09:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684357</loc>
  <lastmod>2026-04-28T11:08:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>楽曲におけるリードと伴奏の分離（An Overview of Lead and Accompaniment Separation in Music）</news:title>
   <news:publication_date>2026-04-28T11:08:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684355</loc>
  <lastmod>2026-04-28T11:07:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>斜め空撮画像からの交差ドメイン建物抽出と選択的深度推定（DEEP CROSS-DOMAIN BUILDING EXTRACTION FOR SELECTIVE DEPTH ESTIMATION FROM OBLIQUE AERIAL IMAGERY）</news:title>
   <news:publication_date>2026-04-28T11:07:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684353</loc>
  <lastmod>2026-04-28T10:16:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メモリマッチングネットワークによるワンショット画像認識（Memory Matching Networks for One-Shot Image Recognition）</news:title>
   <news:publication_date>2026-04-28T10:16:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684351</loc>
  <lastmod>2026-04-28T10:16:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>絵文字とハッシュタグで感情を学ぶ手法の実務的意義（PlusEmo2Vec at SemEval-2018 Task 1: Exploiting emotion knowledge from emoji and #hashtags）</news:title>
   <news:publication_date>2026-04-28T10:16:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684349</loc>
  <lastmod>2026-04-28T10:15:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層意味ハッシュとGANによる合成データ生成（Deep Semantic Hashing with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-04-28T10:15:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684347</loc>
  <lastmod>2026-04-28T10:15:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ転送ユニットによる深層ニューラルネットワークの汎化改善（Parameter Transfer Unit for Deep Neural Networks）</news:title>
   <news:publication_date>2026-04-28T10:15:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684345</loc>
  <lastmod>2026-04-28T10:14:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子カルテに基づく臨床支援の自動化（Clinical Assistant Diagnosis for Electronic Medical Record Based on Convolutional Neural Network）</news:title>
   <news:publication_date>2026-04-28T10:14:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684343</loc>
  <lastmod>2026-04-28T10:14:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味知識の転移による議論理解（NLITrans at SemEval-2018 Task 12: Transfer of Semantic Knowledge for Argument Comprehension）</news:title>
   <news:publication_date>2026-04-28T10:14:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684341</loc>
  <lastmod>2026-04-28T10:14:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>キャプションから動画を生成する技術の衝撃（To Create What You Tell: Generating Videos from Captions）</news:title>
   <news:publication_date>2026-04-28T10:14:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684339</loc>
  <lastmod>2026-04-28T09:22:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>N-fold SuperpositionによるCNNのノイズ低減と収束改善（N-fold Superposition: Improving Neural Networks by Reducing the Noise in Feature Maps）</news:title>
   <news:publication_date>2026-04-28T09:22:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684337</loc>
  <lastmod>2026-04-28T09:22:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Memory Attention Networksによるスケルトン行動認識の革新（Memory Attention Networks for Skeleton-based Action Recognition）</news:title>
   <news:publication_date>2026-04-28T09:22:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684335</loc>
  <lastmod>2026-04-28T09:22:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運転者の適応的性能評価――行動的アドバンテージによる比較（Adaptive Performance Assessment For Drivers Through Behavioral Advantage）</news:title>
   <news:publication_date>2026-04-28T09:22:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684333</loc>
  <lastmod>2026-04-28T09:21:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mem2Seqで対話システムに知識ベースを組み込む（Mem2Seq: Effectively Incorporating Knowledge Bases into End-to-End Task-Oriented Dialog Systems）</news:title>
   <news:publication_date>2026-04-28T09:21:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684331</loc>
  <lastmod>2026-04-28T09:21:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オピエートのµ-オピオイド受容体への結合経路を無監督機械学習で解明（Binding Pathway of Opiates to µ-Opioid Receptors Revealed by Unsupervised Machine Learning）</news:title>
   <news:publication_date>2026-04-28T09:21:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684329</loc>
  <lastmod>2026-04-28T09:21:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語情報を組み込んだ自己注意による意味役割付与（Linguistically-Informed Self-Attention for Semantic Role Labeling）</news:title>
   <news:publication_date>2026-04-28T09:21:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684327</loc>
  <lastmod>2026-04-28T09:21:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Knowledge-based end-to-end memory networks（Knowledge-based end-to-end memory networks）</news:title>
   <news:publication_date>2026-04-28T09:21:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684325</loc>
  <lastmod>2026-04-28T08:29:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模受容野ネットワークによる高倍率画像超解像（Large Receptive Field Networks for High-Scale Image Super-Resolution）</news:title>
   <news:publication_date>2026-04-28T08:29:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684323</loc>
  <lastmod>2026-04-28T08:29:29Z</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・インタリンガによる多言語機械翻訳（A neural interlingua for multilingual machine translation）</news:title>
   <news:publication_date>2026-04-28T08:29:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684321</loc>
  <lastmod>2026-04-28T08:29:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>肺がん診断における深層畳み込みニューラルネットワーク（A Deep Convolutional Neural Network for Lung Cancer Diagnostic）</news:title>
   <news:publication_date>2026-04-28T08:29:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684319</loc>
  <lastmod>2026-04-28T08:28:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NE-Table: ネームドエンティティ向けニューラル鍵値テーブル（NE-Table: A Neural key-value table for Named Entities）</news:title>
   <news:publication_date>2026-04-28T08:28:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684317</loc>
  <lastmod>2026-04-28T08:27:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>悪意あるメール添付ファイル検出エンジンの可能性（MEADE: Towards a Malicious Email Attachment Detection Engine）</news:title>
   <news:publication_date>2026-04-28T08:27:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684315</loc>
  <lastmod>2026-04-28T08:27:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所的白質構造が機能的脳ダイナミクスを規定する（Local White Matter Architecture Defines Functional Brain Dynamics）</news:title>
   <news:publication_date>2026-04-28T08:27:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684313</loc>
  <lastmod>2026-04-28T08:27:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>I Know How You Feel: Emotion Recognition with Facial Landmarks（I Know How You Feel: Emotion Recognition with Facial Landmarks）</news:title>
   <news:publication_date>2026-04-28T08:27:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684311</loc>
  <lastmod>2026-04-28T07:36:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Micro-Net による顕微鏡画像セグメンテーションの統一モデル（Micro-Net: A unified model for segmentation of various objects in microscopy images）</news:title>
   <news:publication_date>2026-04-28T07:36:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684309</loc>
  <lastmod>2026-04-28T07:35:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイキングニューラルネットワークにおける深層学習（Deep Learning in Spiking Neural Networks）</news:title>
   <news:publication_date>2026-04-28T07:35:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684307</loc>
  <lastmod>2026-04-28T07:35:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同じ表現、異なる注意（Same Representation, Different Attentions）</news:title>
   <news:publication_date>2026-04-28T07:35:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684305</loc>
  <lastmod>2026-04-28T07:35:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>訓練データの隠れたバイアスが評価を歪める（Performance Impact Caused by Hidden Bias of Training Data for Recognizing Textual Entailment）</news:title>
   <news:publication_date>2026-04-28T07:35:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684303</loc>
  <lastmod>2026-04-28T07:34:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>英語ツイートにおける皮肉検出手法の実践（IIIDYT at SemEval-2018 Task 3: Irony detection in English tweets）</news:title>
   <news:publication_date>2026-04-28T07:34:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684301</loc>
  <lastmod>2026-04-28T07:34:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストリーミングデータからのスパースな走行時間推定（Sparse Travel Time Estimation from Streaming Data）</news:title>
   <news:publication_date>2026-04-28T07:34:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684299</loc>
  <lastmod>2026-04-28T07:33:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データ下でのベイジアンネットワーク構造学習の高速化（Learning Bayesian Networks from Big Data with Greedy Search）</news:title>
   <news:publication_date>2026-04-28T07:33:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684297</loc>
  <lastmod>2026-04-28T06:43:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アンカーベースNearest Class Mean損失によるCNNの識別性能強化（Anchor-based Nearest Class Mean Loss for Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-04-28T06:43:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684295</loc>
  <lastmod>2026-04-28T06:42:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散的な語義選択を微分可能にする手法の要点（Gumbel Attention for Sense Induction）</news:title>
   <news:publication_date>2026-04-28T06:42:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684293</loc>
  <lastmod>2026-04-28T06:42:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カッコウ探索（Cuckoo Search: State-of-the-Art and Opportunities）</news:title>
   <news:publication_date>2026-04-28T06:42:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684291</loc>
  <lastmod>2026-04-28T06:42:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MQGrad: パラメータサーバにおける勾配量子化を強化学習で制御する手法（MQGrad: Reinforcement Learning of Gradient Quantization in Parameter Server）</news:title>
   <news:publication_date>2026-04-28T06:42:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684289</loc>
  <lastmod>2026-04-28T06:41:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文の位置予測で学ぶ文章埋め込みが変える可読性評価（Learning Sentence Embeddings for Coherence Modelling and Beyond）</news:title>
   <news:publication_date>2026-04-28T06:41:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684287</loc>
  <lastmod>2026-04-28T06:41:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な離散文表現を用いた対話生成（Unsupervised Discrete Sentence Representation Learning for Interpretable Neural Dialog Generation）</news:title>
   <news:publication_date>2026-04-28T06:41:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684285</loc>
  <lastmod>2026-04-28T06:41:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デカップルドネットワーク（Decoupled Networks）</news:title>
   <news:publication_date>2026-04-28T06:41:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684283</loc>
  <lastmod>2026-04-28T05:49:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Bridgeout: 深層ニューラルネットワークの適応的確率的正則化（Bridgeout: stochastic bridge regularization for deep neural networks）</news:title>
   <news:publication_date>2026-04-28T05:49:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684281</loc>
  <lastmod>2026-04-28T05:49:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HeteroMedによる電子カルテ解析の新視点（HeteroMed: Heterogeneous Information Network for Medical Diagnosis）</news:title>
   <news:publication_date>2026-04-28T05:49:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684279</loc>
  <lastmod>2026-04-28T05:49:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語における敵対的サンプル生成（Generating Natural Language Adversarial Examples）</news:title>
   <news:publication_date>2026-04-28T05:49:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684277</loc>
  <lastmod>2026-04-28T05:48:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的メタ埋め込みによる文表現の改善（Dynamic Meta-Embeddings for Improved Sentence Representations）</news:title>
   <news:publication_date>2026-04-28T05:48:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684275</loc>
  <lastmod>2026-04-28T05:48:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neural‑DavidsonianによるSemantic Proto‑role Labelingの新展開（Neural‑Davidsonian Semantic Proto‑role Labeling）</news:title>
   <news:publication_date>2026-04-28T05:48:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684273</loc>
  <lastmod>2026-04-28T05:48:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文字列カーネルと単語埋め込みを組み合わせた自動エッセイ採点（Automated essay scoring with string kernels and word embeddings）</news:title>
   <news:publication_date>2026-04-28T05:48:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684271</loc>
  <lastmod>2026-04-28T04:56:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成対抗ネットワークを用いた空間画像ステガノグラフィ（Spatial Image Steganography Based on Generative Adversarial Network）</news:title>
   <news:publication_date>2026-04-28T04:56:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684269</loc>
  <lastmod>2026-04-28T04:47:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語彙表現とベクトル空間の拡張（Extrofitting: Enriching Word Representation and its Vector Space with Semantic Lexicons）</news:title>
   <news:publication_date>2026-04-28T04:47:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684267</loc>
  <lastmod>2026-04-28T04:47:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PAMに対する焼き直し不要の変分推論——aviPAMがもたらす探索速度の革命（Variational Inference In Pachinko Allocation Machines）</news:title>
   <news:publication_date>2026-04-28T04:47:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684265</loc>
  <lastmod>2026-04-28T04:45:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>訓練可能なGreedyデコーディングの安定的かつ有効な学習戦略（A Stable and Effective Learning Strategy for Trainable Greedy Decoding）</news:title>
   <news:publication_date>2026-04-28T04:45:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684263</loc>
  <lastmod>2026-04-28T04:45:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全空間マルチタスクモデルによるポストクリック転換率推定（Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion Rate）</news:title>
   <news:publication_date>2026-04-28T04:45:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684261</loc>
  <lastmod>2026-04-28T04:45:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴選択は学習データ汚染に耐えられるか（Is Feature Selection Secure against Training Data Poisoning?）</news:title>
   <news:publication_date>2026-04-28T04:45:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684259</loc>
  <lastmod>2026-04-28T04:44:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汎用的な文表現を学ぶマルチタスク学習（Multi-task Learning for Universal Sentence Embeddings: A Thorough Evaluation using Transfer and Auxiliary Tasks）</news:title>
   <news:publication_date>2026-04-28T04:44:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684257</loc>
  <lastmod>2026-04-28T03:52:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>姿勢推定の精度を最後に伸ばす一手：PoseRefiner（Learning to Refine Human Pose Estimation）</news:title>
   <news:publication_date>2026-04-28T03:52:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684255</loc>
  <lastmod>2026-04-28T03:52:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空を量子状態の最適生成ネットワークとして：QM=GRへのロードマップ（Spacetime as the optimal generative network of quantum states: a roadmap to QM=GR?）</news:title>
   <news:publication_date>2026-04-28T03:52:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684253</loc>
  <lastmod>2026-04-28T03:51:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼カメラによる車両位置特定の実用化可能性（Monocular Vision-based Vehicle Localization Aided by Fine-grained Classification）</news:title>
   <news:publication_date>2026-04-28T03:51:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684251</loc>
  <lastmod>2026-04-28T03:51:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン公衆衛生介入のためのソーシャルボット（Social Bots for Online Public Health Interventions）</news:title>
   <news:publication_date>2026-04-28T03:51:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684249</loc>
  <lastmod>2026-04-28T03:51:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>韓国における大気汚染予測にLSTMを用いる深層学習アプローチ（A Deep Learning Approach for Forecasting Air Pollution in South Korea Using LSTM）</news:title>
   <news:publication_date>2026-04-28T03:51:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684247</loc>
  <lastmod>2026-04-28T03:51:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的アンサンブル選択とK-NNの比較（Dynamic Ensemble Selection VS K-NN: why and when Dynamic Selection obtains higher classification performance?）</news:title>
   <news:publication_date>2026-04-28T03:51:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684245</loc>
  <lastmod>2026-04-28T03:50:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的敵対的模倣学習によるイベント抽出（Event Extraction with Generative Adversarial Imitation Learning）</news:title>
   <news:publication_date>2026-04-28T03:50:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684243</loc>
  <lastmod>2026-04-28T02:58:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習による自動車のレーンチェンジ制御（A Reinforcement Learning Based Approach for Automated Lane Change Maneuvers）</news:title>
   <news:publication_date>2026-04-28T02:58:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684241</loc>
  <lastmod>2026-04-28T02:57:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低リソース言語への大規模並列クロスリンガル学習（Massively Parallel Cross-Lingual Learning in Low-Resource Target Language Translation）</news:title>
   <news:publication_date>2026-04-28T02:57:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684239</loc>
  <lastmod>2026-04-28T02:57:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多言語共通セマンティックスペースの構築（Multi-lingual Common Semantic Space Construction via Cluster-consistent Word Embedding）</news:title>
   <news:publication_date>2026-04-28T02:57:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684237</loc>
  <lastmod>2026-04-28T02:56:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層型対話方策学習のためのサブゴール発見（Subgoal Discovery for Hierarchical Dialogue Policy Learning）</news:title>
   <news:publication_date>2026-04-28T02:56:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684235</loc>
  <lastmod>2026-04-28T02:56:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>28nm CMOSで実装した64kシナプス・256ニューロンのオンライン学習型デジタルスパイキングニューロモルフィックプロセッサ（A 0.086-mm2 12.7-pJ/SOP 64k-Synapse 256-Neuron Online-Learning Digital Spiking Neuromorphic Processor in 28nm CMOS）</news:title>
   <news:publication_date>2026-04-28T02:56:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684233</loc>
  <lastmod>2026-04-28T02:56:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CLEVER評価法とグラディエントマスキングの落とし穴（GRADIENT MASKING CAUSES CLEVER TO OVERESTIMATE ADVERSARIAL PERTURBATION SIZE）</news:title>
   <news:publication_date>2026-04-28T02:56:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684231</loc>
  <lastmod>2026-04-28T02:55:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遮蔽された対象の再構成による現場可視化（Occluded Object Reconstruction for First Responders with Augmented Reality Glasses）</news:title>
   <news:publication_date>2026-04-28T02:55:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684229</loc>
  <lastmod>2026-04-28T02:04:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル構文解析器の内部で何が起きているか（What’s Going On in Neural Constituency Parsers? An Analysis）</news:title>
   <news:publication_date>2026-04-28T02:04:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684227</loc>
  <lastmod>2026-04-28T02:04:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CactusNetによる層適用度の定義と転移学習への応用（CactusNets: Layer Applicability as a Metric for Transfer Learning）</news:title>
   <news:publication_date>2026-04-28T02:04:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684225</loc>
  <lastmod>2026-04-28T02:04:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepPETによるPET画像再構成の直接解法 (DeepPET: A deep encoder–decoder network for directly solving the PET reconstruction inverse problem)</news:title>
   <news:publication_date>2026-04-28T02:04:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684223</loc>
  <lastmod>2026-04-28T02:02:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似オラクルを使ったオンライン不適切学習の効率化（Online Improper Learning with an Approximation Oracle）</news:title>
   <news:publication_date>2026-04-28T02:02:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684221</loc>
  <lastmod>2026-04-28T02:02:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>直接ネットワーク転移による文埋め込みの転移学習（Direct Network Transfer: Transfer Learning of Sentence Embeddings for Semantic Similarity）</news:title>
   <news:publication_date>2026-04-28T02:02:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684219</loc>
  <lastmod>2026-04-28T02:01:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前・側面同時処理による胸部X線の自動読影（Large Scale Automated Reading of Frontal and Lateral Chest X-Rays using Dual Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-04-28T02:01:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684217</loc>
  <lastmod>2026-04-28T02:01:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な文脈化表現：系列ラベリングのための言語モデル剪定（Efficient Contextualized Representation: Language Model Pruning for Sequence Labeling）</news:title>
   <news:publication_date>2026-04-28T02:01:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684215</loc>
  <lastmod>2026-04-28T01:09:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>値認識量子化による低精度学習と推論の最適化（Value-aware Quantization for Training and Inference of Neural Networks）</news:title>
   <news:publication_date>2026-04-28T01:09:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684213</loc>
  <lastmod>2026-04-28T01:03:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Autotuneによるハイパーパラメータ調整の自動化 (Autotune: A Derivative-free Optimization Framework for Hyperparameter Tuning)</news:title>
   <news:publication_date>2026-04-28T01:03:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684203</loc>
  <lastmod>2026-04-28T01:02:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視点に依存しない物体カウントのための集約型多列拡張畳み込みネットワーク（An Aggregated Multicolumn Dilated Convolution Network for Perspective-Free Counting）</news:title>
   <news:publication_date>2026-04-28T01:02:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684201</loc>
  <lastmod>2026-04-28T01:02:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化データからの記述生成を変えた二焦点注意機構と直交ゲート（Generating Descriptions from Structured Data Using a Bifocal Attention Mechanism and Gated Orthogonalization）</news:title>
   <news:publication_date>2026-04-28T01:02:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684199</loc>
  <lastmod>2026-04-28T01:01:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔属性予測を組み合わせた深層顔認証ネットワーク（A Deep Face Identification Network Enhanced by Facial Attributes Prediction）</news:title>
   <news:publication_date>2026-04-28T01:01:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684197</loc>
  <lastmod>2026-04-28T01:01:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層表現を使った遠隔監督による臨床情報抽出の新手法（A Deep Representation Empowered Distant Supervision Paradigm for Clinical Information Extraction）</news:title>
   <news:publication_date>2026-04-28T01:01:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684195</loc>
  <lastmod>2026-04-28T00:59:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的サブグラデient法は非滑らかな関数でも収束するのか（Stochastic subgradient method converges on tame functions）</news:title>
   <news:publication_date>2026-04-28T00:59:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684193</loc>
  <lastmod>2026-04-28T00:07:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最も寒い褐色矮星のLバンド分光（AN L BAND SPECTRUM OF THE COLDEST BROWN DWARF）</news:title>
   <news:publication_date>2026-04-28T00:07:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684191</loc>
  <lastmod>2026-04-28T00:07:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PEORL：記号的計画と階層強化学習の統合による頑健な意思決定（PEORL: Integrating Symbolic Planning and Hierarchical Reinforcement Learning for Robust Decision-Making）</news:title>
   <news:publication_date>2026-04-28T00:07:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684189</loc>
  <lastmod>2026-04-28T00:07:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インタラクティブモバイルアプリを用いた授業外のアクティブラーニング（Active Learning for Out-of-class Activities by Using Interactive Mobile Apps）</news:title>
   <news:publication_date>2026-04-28T00:07:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684187</loc>
  <lastmod>2026-04-28T00:06:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モノリンガルだけで翻訳を学ぶ手法（Phrase-Based &amp;amp; Neural Unsupervised Machine Translation）</news:title>
   <news:publication_date>2026-04-28T00:06:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684185</loc>
  <lastmod>2026-04-28T00:06:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話から学ぶ文の意味的類似性（Learning Semantic Textual Similarity from Conversations）</news:title>
   <news:publication_date>2026-04-28T00:06:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684183</loc>
  <lastmod>2026-04-28T00:05:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リーマン・シータ・ボルツマンマシンのサンプリング手法（Sampling the Riemann-Theta Boltzmann Machine）</news:title>
   <news:publication_date>2026-04-28T00:05:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684181</loc>
  <lastmod>2026-04-28T00:05:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>XMM-LSS領域におけるX線点源カタログの整備（XMM-LSS X-ray Point-Source Catalog）</news:title>
   <news:publication_date>2026-04-28T00:05:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684179</loc>
  <lastmod>2026-04-27T23:14:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>退屈な粒子の正体を見分けるAI――重い縮退ヒッグスの信号混合推定に深層ニューラルネットワークを用いる試み（Signal mixture estimation for degenerate heavy Higgses using a deep neural network）</news:title>
   <news:publication_date>2026-04-27T23:14:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684177</loc>
  <lastmod>2026-04-27T23:13:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語埋め込みの言語間写像を「検索基準」で最適化する手法（Loss in Translation: Learning Bilingual Word Mapping with a Retrieval Criterion）</news:title>
   <news:publication_date>2026-04-27T23:13:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684175</loc>
  <lastmod>2026-04-27T23:13:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒッグス真空不安定性から生じる原始黒洞（Primordial Black Holes from Higgs Vacuum Instability: Avoiding Fine-tuning through an Ultraviolet Safe Mechanism）</news:title>
   <news:publication_date>2026-04-27T23:13:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684173</loc>
  <lastmod>2026-04-27T23:11:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トラップドイオン量子ビットの機械学習支援読み出し（Machine learning assisted readout of trapped-ion qubits）</news:title>
   <news:publication_date>2026-04-27T23:11:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684171</loc>
  <lastmod>2026-04-27T23:11:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不規則な穴の画像修復における部分畳み込み（Image Inpainting for Irregular Holes Using Partial Convolutions）</news:title>
   <news:publication_date>2026-04-27T23:11:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684169</loc>
  <lastmod>2026-04-27T23:11:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像に対する敵対的変形攻撃の反復アルゴリズム（ADEF: AN ITERATIVE ALGORITHM TO CONSTRUCT ADVERSARIAL DEFORMATIONS）</news:title>
   <news:publication_date>2026-04-27T23:11:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684167</loc>
  <lastmod>2026-04-27T23:10:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トポロジ駆動によるターゲット影響最大化（Topology-driven Diversity for Targeted Influence Maximization）</news:title>
   <news:publication_date>2026-04-27T23:10:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684165</loc>
  <lastmod>2026-04-27T22:18:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSSTによるPlanet X探索の可検出性（ON THE DETECTABILITY OF PLANET X WITH LSST）</news:title>
   <news:publication_date>2026-04-27T22:18:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684163</loc>
  <lastmod>2026-04-27T22:17:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異なる発話行為とスロットをまたぐ対話ポリシー転移（Cross-domain Dialogue Policy Transfer via Simultaneous Speech-act and Slot Alignment）</news:title>
   <news:publication_date>2026-04-27T22:17:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684161</loc>
  <lastmod>2026-04-27T22:16:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声感情認識におけるドメイン敵対的学習（Domain Adversarial for Acoustic Emotion Recognition）</news:title>
   <news:publication_date>2026-04-27T22:16:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684159</loc>
  <lastmod>2026-04-27T22:15:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークによる顧客オンライン行動モデリング（Modelling customer online behaviours with neural networks: applications to conversion prediction and advertising retargeting）</news:title>
   <news:publication_date>2026-04-27T22:15:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684157</loc>
  <lastmod>2026-04-27T22:15:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的敵対正則化を用いた逆トーンマッピングネットワークの学習 (Learning an Inverse Tone Mapping Network with a Generative Adversarial Regularizer)</news:title>
   <news:publication_date>2026-04-27T22:15:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684155</loc>
  <lastmod>2026-04-27T22:15:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Residual D-netによる脳結合性ダイナミクスの教師なし学習（Unsupervised learning of the brain connectivity dynamic using residual D-net）</news:title>
   <news:publication_date>2026-04-27T22:15:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684153</loc>
  <lastmod>2026-04-27T22:15:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形光ファイバ通信における終端からのオートエンコーダ学習による到達可能情報率（Achievable Information Rates for Nonlinear Fiber Communication via End-to-end Autoencoder Learning）</news:title>
   <news:publication_date>2026-04-27T22:15:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684151</loc>
  <lastmod>2026-04-27T21:23:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超解像超音波局所化顕微鏡と深層学習による実装（Super-resolution Ultrasound Localization Microscopy through Deep Learning）</news:title>
   <news:publication_date>2026-04-27T21:23:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684149</loc>
  <lastmod>2026-04-27T21:22:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>古典的グラフィカルモデルからの量子符号（Quantum Codes from Classical Graphical Models）</news:title>
   <news:publication_date>2026-04-27T21:22:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684147</loc>
  <lastmod>2026-04-27T21:22:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>環境が進化的群ロボティクスの適応機構にもたらす影響の調査 (An Investigation of Environmental Influence on the Benefits of Adaptation Mechanisms in Evolutionary Swarm Robotics)</news:title>
   <news:publication_date>2026-04-27T21:22:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684145</loc>
  <lastmod>2026-04-27T21:21:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周期的活性化関数を持つ簡素な量子ニューラルネット（A Simple Quantum Neural Net with a Periodic Activation Function）</news:title>
   <news:publication_date>2026-04-27T21:21:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684143</loc>
  <lastmod>2026-04-27T21:21:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小バッチ学習を見直す――効率と汎化のトレードオフ（REVISITING SMALL BATCH TRAINING FOR DEEP NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-04-27T21:21:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684141</loc>
  <lastmod>2026-04-27T21:20:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑なデータ位相の堅牢でスケーラブルな学習（ROBUST AND SCALABLE LEARNING OF COMPLEX DATASET TOPOLOGIES VIA ELPIGRAPH）</news:title>
   <news:publication_date>2026-04-27T21:20:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684139</loc>
  <lastmod>2026-04-27T21:20:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイバー防衛に向けた知能的自律エージェントの展望（Toward Intelligent Autonomous Agents for Cyber Defense）</news:title>
   <news:publication_date>2026-04-27T21:20:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684137</loc>
  <lastmod>2026-04-27T20:28:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>左心房セグメンテーションのためのドメイン・幾何学非依存CNN（Domain and Geometry Agnostic CNNs for Left Atrium Segmentation in 3D Ultrasound）</news:title>
   <news:publication_date>2026-04-27T20:28:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684135</loc>
  <lastmod>2026-04-27T20:28:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>赤色巨星における太陽様振動の検出を深層学習で自動化する（Detecting Solar-Like Oscillations in Red Giants with Deep Learning）</news:title>
   <news:publication_date>2026-04-27T20:28:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684133</loc>
  <lastmod>2026-04-27T20:27:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軽量で高速な顔認証を実現するMobileFaceNets（MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices）</news:title>
   <news:publication_date>2026-04-27T20:27:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684131</loc>
  <lastmod>2026-04-27T20:26:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実運用ストリーミング環境における能動学習によるクレジットカード不正検知の評価（Streaming Active Learning Strategies for Real-Life Credit Card Fraud Detection: Assessment and Visualization）</news:title>
   <news:publication_date>2026-04-27T20:26:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684129</loc>
  <lastmod>2026-04-27T20:26:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分ラベル学習に自己ペース正則化を組み合わせる手法の解説（A Self-paced Regularization Framework for Partial-Label Learning）</news:title>
   <news:publication_date>2026-04-27T20:26:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684127</loc>
  <lastmod>2026-04-27T20:26:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ResGuideNetによる単一画像の雨滴除去（Residual-Guide Network for Single Image Deraining）</news:title>
   <news:publication_date>2026-04-27T20:26:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684125</loc>
  <lastmod>2026-04-27T20:25:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNの可視化における正則化の理解（Understanding Regularization to Visualize Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-04-27T20:25:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684123</loc>
  <lastmod>2026-04-27T19:33:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習された特徴をより頑健にする敵対的訓練（Learning More Robust Features with Adversarial Training）</news:title>
   <news:publication_date>2026-04-27T19:33:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684121</loc>
  <lastmod>2026-04-27T19:27:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>D¨IOTによるIoT異常検知の連合自己学習（D¨IOT: A Federated Self-learning Anomaly Detection System for IoT）</news:title>
   <news:publication_date>2026-04-27T19:27:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684119</loc>
  <lastmod>2026-04-27T19:26:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地上画像と携帯GPSだけで達成する高精度ジオローカライゼーション（Accurate Deep Direct Geo-Localization from Ground Imagery and Phone-Grade GPS）</news:title>
   <news:publication_date>2026-04-27T19:26:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684117</loc>
  <lastmod>2026-04-27T19:25:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高いsp3含有率を生む成長機構の解明（Growth mechanism and origin of high sp3 content in tetrahedral amorphous carbon）</news:title>
   <news:publication_date>2026-04-27T19:25:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684115</loc>
  <lastmod>2026-04-27T19:24:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GLUE：自然言語理解の汎用評価基盤（GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding）</news:title>
   <news:publication_date>2026-04-27T19:24:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684113</loc>
  <lastmod>2026-04-27T19:24:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン非定常環境下でのフォグタスクオフロード学習（Learn and Pick Right Nodes to Offload）</news:title>
   <news:publication_date>2026-04-27T19:24:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684111</loc>
  <lastmod>2026-04-27T19:23:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視点適応型ニューラルネットワークによる骨格ベース行動認識の高精度化（View Adaptive Neural Networks for High Performance Skeleton-based Human Action Recognition）</news:title>
   <news:publication_date>2026-04-27T19:23:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684109</loc>
  <lastmod>2026-04-27T18:32:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己触媒で位相一様なp型GaAsナノワイヤによる高感度光検出（High-Responsivity Photodetection by Self-Catalyzed Phase-Pure P-GaAs Nanowire）</news:title>
   <news:publication_date>2026-04-27T18:32:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684107</loc>
  <lastmod>2026-04-27T18:31:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習モデルと専用アクセラレータの協調設計がもたらす変化（Co-Design of Deep Neural Nets and Neural Net Accelerators for Embedded Vision Applications）</news:title>
   <news:publication_date>2026-04-27T18:31:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684105</loc>
  <lastmod>2026-04-27T18:31:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SDN連携で進化するIP/光ネットワーク管理（Two Use Cases of Machine Learning for SDN-Enabled IP/Optical Networks）</news:title>
   <news:publication_date>2026-04-27T18:31:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684103</loc>
  <lastmod>2026-04-27T18:30:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンスハードネスに基づくアンサンブル生成法（An Ensemble Generation Method Based on Instance Hardness）</news:title>
   <news:publication_date>2026-04-27T18:30:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684101</loc>
  <lastmod>2026-04-27T18:30:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心電図の拍動分類と転移可能な深層表現（ECG Heartbeat Classification: A Deep Transferable Representation）</news:title>
   <news:publication_date>2026-04-27T18:30:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684099</loc>
  <lastmod>2026-04-27T18:30:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッド圧電・磁気ニューロン：省エネ機械学習への提案（Hybrid Piezoelectric-Magnetic Neurons: A Proposal for Energy-Efficient Machine Learning）</news:title>
   <news:publication_date>2026-04-27T18:30:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684097</loc>
  <lastmod>2026-04-27T18:30:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GritNetによる学習者成績予測の革新（GritNet: Student Performance Prediction with Deep Learning）</news:title>
   <news:publication_date>2026-04-27T18:30:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684095</loc>
  <lastmod>2026-04-27T17:37:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河系超新星残骸 G179.0+2.6 の光学放射の発見（Optical Emission Associated with the Galactic Supernova Remnant G179.0+2.6）</news:title>
   <news:publication_date>2026-04-27T17:37:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684093</loc>
  <lastmod>2026-04-27T17:37:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模無線ネットワークにおけるQoS（Quality of Service）提供の遅延解析（QoS Provisioning in Large Wireless Networks）</news:title>
   <news:publication_date>2026-04-27T17:37:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684091</loc>
  <lastmod>2026-04-27T17:37:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低精度化と構造的圧縮で最小面積・低消費エネルギーを目指す深層学習ハードウェア設計（Minimizing Area and Energy of Deep Learning Hardware Design Using Collective Low Precision and Structured Compression）</news:title>
   <news:publication_date>2026-04-27T17:37:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684089</loc>
  <lastmod>2026-04-27T17:36:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元ハイパースペクトル画像のランダム化次元削減（Randomized ICA and LDA Dimensionality Reduction Methods for Hyperspectral Image Classification）</news:title>
   <news:publication_date>2026-04-27T17:36:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684087</loc>
  <lastmod>2026-04-27T17:36:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低画質画像に対する顔検出の現状調査（Survey of Face Detection on Low-quality Images）</news:title>
   <news:publication_date>2026-04-27T17:36:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684085</loc>
  <lastmod>2026-04-27T17:36:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GRUにおけるサンプリング不要の不確実性推定（Sampling-free Uncertainty Estimation in Gated Recurrent Units with Exponential Families）</news:title>
   <news:publication_date>2026-04-27T17:36:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684083</loc>
  <lastmod>2026-04-27T17:35:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現学習を双方向でつなぐRepGANの要点（Unsupervised Representation Adversarial Learning Network: from Reconstruction to Generation）</news:title>
   <news:publication_date>2026-04-27T17:35:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684081</loc>
  <lastmod>2026-04-27T16:44:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴選択法の比較と応用—応力ホットスポット分類における実務的示唆（A comparative study of feature selection methods for stress hotspot classification in materials）</news:title>
   <news:publication_date>2026-04-27T16:44:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684079</loc>
  <lastmod>2026-04-27T16:44:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外部データの低次元埋め込みを拡張する数学的解析（Mathematical Analysis on Out-of-Sample Extensions）</news:title>
   <news:publication_date>2026-04-27T16:44:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684077</loc>
  <lastmod>2026-04-27T16:43:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同期していない音声映像イベントの弱教師付き表現学習（Weakly Supervised Representation Learning for Unsynchronized Audio-Visual Events）</news:title>
   <news:publication_date>2026-04-27T16:43:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684075</loc>
  <lastmod>2026-04-27T16:42:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重要度重み付きリスク推定量のサンプリング歪度がモデル選択に与える影響（Effects of sampling skewness of the importance-weighted risk estimator on model selection）</news:title>
   <news:publication_date>2026-04-27T16:42:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684073</loc>
  <lastmod>2026-04-27T16:41:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続状態・行動空間における非パラメトリック確率的合成勾配降下法によるQ学習（Nonparametric Stochastic Compositional Gradient Descent for Q-Learning in Continuous Markov Decision Problems）</news:title>
   <news:publication_date>2026-04-27T16:41:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684071</loc>
  <lastmod>2026-04-27T16:41:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中心的なブルーナゲット段階にある高赤方偏移銀河を深層学習で同定（Deep Learning Identifies High-z Galaxies in a Central Blue Nugget Phase in a Characteristic Mass Range）</news:title>
   <news:publication_date>2026-04-27T16:41:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684069</loc>
  <lastmod>2026-04-27T16:40:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>4次元F-理論における非ヒッグス不変ゲージ群の機械学習による識別（Learning non-Higgsable gauge groups in 4D F-theory）</news:title>
   <news:publication_date>2026-04-27T16:40:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684067</loc>
  <lastmod>2026-04-27T15:49:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファストラジオバーストで銀河間のバリオン（普通物質）分布を計る方法（MEASURING THE CIRCUM- AND INTER-GALACTIC BARYON CONTENTS WITH FAST RADIO BURSTS）</news:title>
   <news:publication_date>2026-04-27T15:49:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684065</loc>
  <lastmod>2026-04-27T15:47:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機能的生成設計（Functional Generative Design: An Evolutionary Approach to 3D-Printing）</news:title>
   <news:publication_date>2026-04-27T15:47:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684063</loc>
  <lastmod>2026-04-27T15:46:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テレスコーピング・ブレグマン型近接勾配法：Lipschitz連続性仮定を外す最適化（A TELESCOPING BREGMANIAN PROXIMAL GRADIENT METHOD WITHOUT THE GLOBAL LIPSCHITZ CONTINUITY ASSUMPTION）</news:title>
   <news:publication_date>2026-04-27T15:46:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684061</loc>
  <lastmod>2026-04-27T15:46:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワンショット学習を現実に近づける深層トリプレットランキング（Deep Triplet Ranking Networks for One-Shot Recognition）</news:title>
   <news:publication_date>2026-04-27T15:46:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684059</loc>
  <lastmod>2026-04-27T15:46:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限られた試行で極値リスクを評価する逐次サンプリング法（A Sequential Sampling Strategy for Extreme Event Statistics in Nonlinear Dynamical Systems）</news:title>
   <news:publication_date>2026-04-27T15:46:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684057</loc>
  <lastmod>2026-04-27T15:45:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人による導きと内発的動機付けを組み合わせたロボット運動スキル学習（Socially Guided Intrinsic Motivation for Robot Learning of Motor Skills）</news:title>
   <news:publication_date>2026-04-27T15:45:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684055</loc>
  <lastmod>2026-04-27T15:44:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層動的ブーステッドフォレスト（Deep Dynamic Boosted Forest）</news:title>
   <news:publication_date>2026-04-27T15:44:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684053</loc>
  <lastmod>2026-04-27T14:53:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>北西南アメリカにおける潮汐と地震活動の相関（Correlation between tides and seismicity in Northwestern South America: the case of Colombia）</news:title>
   <news:publication_date>2026-04-27T14:53:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684051</loc>
  <lastmod>2026-04-27T14:53:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチビューハイブリッド埋め込み（Multi-view Hybrid Embedding: A Divide-and-Conquer Approach）</news:title>
   <news:publication_date>2026-04-27T14:53:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684049</loc>
  <lastmod>2026-04-27T14:53:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>pDCAe による差分凸最適化の収束解析と応用（A refined convergence analysis of pDCAe with applications to simultaneous sparse recovery and outlier detection）</news:title>
   <news:publication_date>2026-04-27T14:53:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684047</loc>
  <lastmod>2026-04-27T14:51:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルベース強化学習におけるリプシッツ連続性（Lipschitz Continuity in Model-based Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-27T14:51:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684045</loc>
  <lastmod>2026-04-27T14:51:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非自律微分方程式から導かれる安定深層ネットワーク（NAIS-NET: Stable Deep Networks from Non-Autonomous Differential Equations）</news:title>
   <news:publication_date>2026-04-27T14:51:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684043</loc>
  <lastmod>2026-04-27T14:50:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Motion Fused Frames：動き情報を静止画に融合することで手話認識を変える（Motion Fused Frames: Data Level Fusion Strategy for Hand Gesture Recognition）</news:title>
   <news:publication_date>2026-04-27T14:50:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684041</loc>
  <lastmod>2026-04-27T14:50:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストの切り分け表現学習と医療要旨への応用（Learning Disentangled Representations of Texts with Application to Biomedical Abstracts）</news:title>
   <news:publication_date>2026-04-27T14:50:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684039</loc>
  <lastmod>2026-04-27T13:58:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声から鳥種を識別する基礎─2018 BirdCLEF ベースラインシステム（Recognizing Birds from Sound - The 2018 BirdCLEF Baseline System）</news:title>
   <news:publication_date>2026-04-27T13:58:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684037</loc>
  <lastmod>2026-04-27T13:58:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車両同士の通信戦略（Vehicle Communication Strategies for Simulated Highway Driving）</news:title>
   <news:publication_date>2026-04-27T13:58:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684035</loc>
  <lastmod>2026-04-27T13:57:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的非教師変形モデルによるロバストな微分同相登録（Unsupervised Probabilistic Deformation Modeling for Robust Diffeomorphic Registration）</news:title>
   <news:publication_date>2026-04-27T13:57:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684033</loc>
  <lastmod>2026-04-27T13:57:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンス選択でGM（幾何平均）が改善する研究（Instance Selection Improves Geometric Mean Accuracy: A Study on Imbalanced Data Classification）</news:title>
   <news:publication_date>2026-04-27T13:57:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684031</loc>
  <lastmod>2026-04-27T13:56:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間活動認識における再帰型ニューラルネットワークの応用（Human Activity Recognition using Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-04-27T13:56:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684029</loc>
  <lastmod>2026-04-27T13:56:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高齢者と専門職の視点から見たAmbient Assisted Living技術（Ambient Assisted Living technologies from the perspectives of older people and professionals）</news:title>
   <news:publication_date>2026-04-27T13:56:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684027</loc>
  <lastmod>2026-04-27T13:55:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模非線形変数選択とカーネルランダム特徴（Large-scale Nonlinear Variable Selection via Kernel Random Features）</news:title>
   <news:publication_date>2026-04-27T13:55:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684025</loc>
  <lastmod>2026-04-27T13:04:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>varrank: 相互情報量に基づく変数ランク付けのRパッケージ（varrank: an R package for variable ranking based on mutual information）</news:title>
   <news:publication_date>2026-04-27T13:04:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684023</loc>
  <lastmod>2026-04-27T13:04:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像処理のための可視性グラフ（Visibility graphs for image processing）</news:title>
   <news:publication_date>2026-04-27T13:04:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684021</loc>
  <lastmod>2026-04-27T13:04:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的行動レパートリーと教師なし記述子（Hierarchical Behavioral Repertoires with Unsupervised Descriptors）</news:title>
   <news:publication_date>2026-04-27T13:04:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684019</loc>
  <lastmod>2026-04-27T13:03:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>辞書学習—局所からグローバルへ、そして適応へ（Dictionary learning - from local towards global and adaptive）</news:title>
   <news:publication_date>2026-04-27T13:03:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684017</loc>
  <lastmod>2026-04-27T13:02:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>速度—空隙率スーパーモデル（Velocity-Porosity Supermodel）</news:title>
   <news:publication_date>2026-04-27T13:02:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684015</loc>
  <lastmod>2026-04-27T13:02:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>H&amp;amp;Eを用いた前立腺癌の無監督検出（Unsupervised Prostate Cancer Detection on H&amp;amp;E using Convolutional Adversarial Autoencoders）</news:title>
   <news:publication_date>2026-04-27T13:02:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684013</loc>
  <lastmod>2026-04-27T13:01:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限な偏りを用いた無限概念クラスの教授法（Finite Biased Teaching with Infinite Concept Classes）</news:title>
   <news:publication_date>2026-04-27T13:01:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684011</loc>
  <lastmod>2026-04-27T12:10:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実務にQ&amp;amp;Aを導入するための転移学習とメタデータ活用（Putting Question-Answering Systems into Practice: Transfer Learning for Efficient Domain Customization）</news:title>
   <news:publication_date>2026-04-27T12:10:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684009</loc>
  <lastmod>2026-04-27T12:10:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Part-Aligned Bilinear Representations for Person Re-identification（Part-Aligned Bilinear Representations for Person Re-identification）</news:title>
   <news:publication_date>2026-04-27T12:10:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684007</loc>
  <lastmod>2026-04-27T12:09:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最大発散領域を検出する時空間異常検出手法（Detecting Regions of Maximal Divergence for Spatio-Temporal Anomaly Detection）</news:title>
   <news:publication_date>2026-04-27T12:09:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684005</loc>
  <lastmod>2026-04-27T12:08:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランク表現による頑健化（Robustness via Deep Low-Rank Representations）</news:title>
   <news:publication_date>2026-04-27T12:08:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684003</loc>
  <lastmod>2026-04-27T12:08:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク機能仮想化の多時間スケールオンライン最適化（Multi-Timescale Online Optimization of Network Function Virtualization for Service Chaining）</news:title>
   <news:publication_date>2026-04-27T12:08:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/684001</loc>
  <lastmod>2026-04-27T12:08:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>星形成のコア密度分布を見分ける新手法（A NEW METHOD TO QUANTIFY DIFFERENTIATE COLLAPSE MODELS OF STAR FORMATION）</news:title>
   <news:publication_date>2026-04-27T12:08:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683999</loc>
  <lastmod>2026-04-27T12:07:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測ネットワーク探索と非パラメトリック・バンディット（Exploring Partially Observed Networks with Nonparametric Bandits）</news:title>
   <news:publication_date>2026-04-27T12:07:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683997</loc>
  <lastmod>2026-04-27T11:16:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プラズモニック構造の共鳴特性予測（Predicting resonant properties of plasmonic structures by deep learning）</news:title>
   <news:publication_date>2026-04-27T11:16:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683995</loc>
  <lastmod>2026-04-27T11:15:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セマンティック敵対的深層学習（Semantic Adversarial Deep Learning）</news:title>
   <news:publication_date>2026-04-27T11:15:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683993</loc>
  <lastmod>2026-04-27T11:15:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースMCSにおける深層強化学習によるセル選択（Cell Selection with Deep Reinforcement Learning in Sparse Mobile Crowdsensing）</news:title>
   <news:publication_date>2026-04-27T11:15:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683991</loc>
  <lastmod>2026-04-27T11:14:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元偏微分方程式を解く深層学習とFBSDEの手法（Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations）</news:title>
   <news:publication_date>2026-04-27T11:14:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683989</loc>
  <lastmod>2026-04-27T11:14:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一貫性のある要約抽出を学習する手法（Learning to Extract Coherent Summary via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-27T11:14:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683987</loc>
  <lastmod>2026-04-27T11:14:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シミュレーション由来の物理場再構築（Reconstruction of Simulation-Based Physical Field by Reconstruction Neural Network Method）</news:title>
   <news:publication_date>2026-04-27T11:14:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683985</loc>
  <lastmod>2026-04-27T11:13:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大マージン構造畳み込み演算子によるサーマル赤外追跡（Large Margin Structured Convolution Operator for Thermal Infrared Object Tracking）</news:title>
   <news:publication_date>2026-04-27T11:13:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683983</loc>
  <lastmod>2026-04-27T10:22:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>赤外線と可視画像の深層学習による融合法（Infrared and Visible Image Fusion using a Deep Learning Framework）</news:title>
   <news:publication_date>2026-04-27T10:22:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683981</loc>
  <lastmod>2026-04-27T10:21:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストからうつ傾向を早期検出する手法の要点解説（Utilizing Neural Networks and Linguistic Metadata for Early Detection of Depression Indications in Text Sequences）</news:title>
   <news:publication_date>2026-04-27T10:21:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683979</loc>
  <lastmod>2026-04-27T10:21:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GNASによる貪欲なニューラルアーキテクチャ探索（GNAS: A Greedy Neural Architecture Search Method for Multi-Attribute Learning）</news:title>
   <news:publication_date>2026-04-27T10:21:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683977</loc>
  <lastmod>2026-04-27T10:20:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Adversarial Complementary Learningによる弱教師あり物体局所化（Adversarial Complementary Learning for Weakly Supervised Object Localization）</news:title>
   <news:publication_date>2026-04-27T10:20:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683975</loc>
  <lastmod>2026-04-27T10:20:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散シミュレーションと分散推論（Distributed Simulation and Distributed Inference）</news:title>
   <news:publication_date>2026-04-27T10:20:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683973</loc>
  <lastmod>2026-04-27T10:20:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>操作可能な要因と非操作要因を分離する手法（Disentangling Controllable and Uncontrollable Factors of Variation by Interacting with the World）</news:title>
   <news:publication_date>2026-04-27T10:20:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683971</loc>
  <lastmod>2026-04-27T10:19:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一次宇宙線の局所銀河間スペクトルの解読（Deciphering the Local Interstellar Spectra of Primary Cosmic Ray Species with HELMOD）</news:title>
   <news:publication_date>2026-04-27T10:19:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683969</loc>
  <lastmod>2026-04-27T09:28:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>境界領域を守る近傍オラクル法：KNORA-B / KNORA-BI（K-Nearest Oracles Borderline）</news:title>
   <news:publication_date>2026-04-27T09:28:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683967</loc>
  <lastmod>2026-04-27T09:28:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>次世代エクサゲームに向けたテニススイングの個別化評価手法（Towards the next generation of exergames: Flexible and personalised assessment-based identification of tennis swings）</news:title>
   <news:publication_date>2026-04-27T09:28:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683965</loc>
  <lastmod>2026-04-27T09:27:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゼロから始める一枚学習：Mixture of Variational Autoencoders（One-Shot Learning using Mixture of Variational Autoencoders: a Generalization Learning approach）</news:title>
   <news:publication_date>2026-04-27T09:27:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683963</loc>
  <lastmod>2026-04-27T09:27:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMで生成するポリフォニック音楽の設計と評価（Generating Music using an LSTM Network）</news:title>
   <news:publication_date>2026-04-27T09:27:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683961</loc>
  <lastmod>2026-04-27T09:27:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像補間による映像圧縮（Video Compression through Image Interpolation）</news:title>
   <news:publication_date>2026-04-27T09:27:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683959</loc>
  <lastmod>2026-04-27T09:26:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>開口を通過する液滴の局所速度変動（Local velocity variations for a drop moving through an orifice）</news:title>
   <news:publication_date>2026-04-27T09:26:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683957</loc>
  <lastmod>2026-04-27T09:26:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分的に注釈されたデータを活用した時間関係抽出（Exploiting Partially Annotated Data for Temporal Relation Extraction）</news:title>
   <news:publication_date>2026-04-27T09:26:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683955</loc>
  <lastmod>2026-04-27T08:35:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少データ環境における高関連経路推薦システム（Highly Relevant Routing Recommendation Systems for Handling Few Data Using MDL Principle and Embedded Relevance Boosting Factors）</news:title>
   <news:publication_date>2026-04-27T08:35:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683953</loc>
  <lastmod>2026-04-27T08:35:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動採点モデルの弱点と局所コヒーレンスの補強（Neural Automated Essay Scoring and Coherence Modeling for Adversarially Crafted Input）</news:title>
   <news:publication_date>2026-04-27T08:35:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683951</loc>
  <lastmod>2026-04-27T08:34:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フィードバックループによる偏りを同時に除去する手法（Modeling and Simultaneously Removing Bias via Adversarial Neural Networks）</news:title>
   <news:publication_date>2026-04-27T08:34:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683949</loc>
  <lastmod>2026-04-27T08:34:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル向けリアルタイム物体検出の実装と効率化（Pelee: A Real-Time Object Detection System on Mobile Devices）</news:title>
   <news:publication_date>2026-04-27T08:34:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683947</loc>
  <lastmod>2026-04-27T08:34:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープ強化学習における過学習の実態（A Study on Overfitting in Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-27T08:34:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683945</loc>
  <lastmod>2026-04-27T08:34:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Co-teachingによるノイズラベルに強い深層学習（Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels）</news:title>
   <news:publication_date>2026-04-27T08:34:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683943</loc>
  <lastmod>2026-04-27T08:33:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コロイド粒子のホログラムにおける高速かつ高精度な特徴局在のための機械学習手法（Machine-learning techniques for fast and accurate feature localization in holograms of colloidal particles）</news:title>
   <news:publication_date>2026-04-27T08:33:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683941</loc>
  <lastmod>2026-04-27T07:42:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈依存文を実行可能な形式クエリへ学習する（Learning to Map Context-Dependent Sentences to Executable Formal Queries）</news:title>
   <news:publication_date>2026-04-27T07:42:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683939</loc>
  <lastmod>2026-04-27T07:34:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>血管内超音波画像における脆弱プラークの自動検出（Automated detection of vulnerable plaque in intravascular ultrasound images）</news:title>
   <news:publication_date>2026-04-27T07:34:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683937</loc>
  <lastmod>2026-04-27T07:31:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極端な[Oiii]放射体におけるライマン連続放射の低い逃逸率（A Low Lyman Continuum Escape Fraction of &amp;lt; 10% for Extreme [Oiii] Emitters in an Overdensity at z∼3.5）</news:title>
   <news:publication_date>2026-04-27T07:31:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683935</loc>
  <lastmod>2026-04-27T07:31:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遺伝子型空間のネットワーク化された構造と分子進化への臨界的影響（On the networked architecture of genotype spaces and its critical effects on molecular evolution）</news:title>
   <news:publication_date>2026-04-27T07:31:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683933</loc>
  <lastmod>2026-04-27T07:30:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層特徴を活かす追跡技術の再定義（Unveiling the Power of Deep Tracking）</news:title>
   <news:publication_date>2026-04-27T07:30:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683931</loc>
  <lastmod>2026-04-27T07:29:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>社会的指導を受けるロボットの能動的教師選択と目標設定（Active Choice of Teachers, Learning Strategies and Goals for a Socially Guided Intrinsic Motivation Learner）</news:title>
   <news:publication_date>2026-04-27T07:29:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683929</loc>
  <lastmod>2026-04-27T07:29:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層畳み込みエンコーダ–デコーダネットワークによる地震層準追跡の自動化（A deep convolutional encoder-decoder neural network in assisting seismic horizon tracking）</news:title>
   <news:publication_date>2026-04-27T07:29:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683927</loc>
  <lastmod>2026-04-27T06:38:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シンボリック回帰木の指数的成長を抑える手法（Solving the Exponential Growth of Symbolic Regression Trees in Geometric Semantic Genetic Programming）</news:title>
   <news:publication_date>2026-04-27T06:38:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683925</loc>
  <lastmod>2026-04-27T06:37:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フラクショナル・ブラウン運動で星団構造をモデル化する手法（Modelling the structure of star clusters with fractional Brownian motion）</news:title>
   <news:publication_date>2026-04-27T06:37:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683923</loc>
  <lastmod>2026-04-27T06:37:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心電図を画像化してCNNで分類する手法の実務的意義（ECG arrhythmia classification using deep two-dimensional convolutional neural network）</news:title>
   <news:publication_date>2026-04-27T06:37:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683921</loc>
  <lastmod>2026-04-27T06:37:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声スペクトルのサブバンドを揺らすことで学習が改善する（SHAKING ACOUSTIC SPECTRAL SUB-BANDS CAN BETTER REGULARIZE LEARNING IN AFFECTIVE COMPUTING）</news:title>
   <news:publication_date>2026-04-27T06:37:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683919</loc>
  <lastmod>2026-04-27T06:36:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模グラフのエントロピック・スペクトル学習（Entropic Spectral Learning for Large-Scale Graphs）</news:title>
   <news:publication_date>2026-04-27T06:36:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683917</loc>
  <lastmod>2026-04-27T06:36:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言葉とトピックの視覚的具体性を定量化する手法（Quantifying the visual concreteness of words and topics in multimodal datasets）</news:title>
   <news:publication_date>2026-04-27T06:36:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683915</loc>
  <lastmod>2026-04-27T06:36:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>期待バイアス付きLSTMによる長期予測の改善（Improving Long-Horizon Forecasts with Expectation-Biased LSTM Networks）</news:title>
   <news:publication_date>2026-04-27T06:36:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683913</loc>
  <lastmod>2026-04-27T05:45:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>神経模倣型抵抗メモリにおける高次シナプス学習 (High order synaptic learning in neuro-mimicking resistive memories)</news:title>
   <news:publication_date>2026-04-27T05:45:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683911</loc>
  <lastmod>2026-04-27T05:37:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし音声コンテキスト埋め込み（Unspeech: Unsupervised Speech Context Embeddings）</news:title>
   <news:publication_date>2026-04-27T05:37:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683909</loc>
  <lastmod>2026-04-27T05:36:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シミュレーションベースの敵対的テスト生成による自動運転車の検証（Simulation-based Adversarial Test Generation for Autonomous Vehicles with Machine Learning Components）</news:title>
   <news:publication_date>2026-04-27T05:36:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683907</loc>
  <lastmod>2026-04-27T05:36:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CoNet：クロスドメイン推薦のための協調的クロスネットワーク（CoNet: Collaborative Cross Networks for Cross-Domain Recommendation）</news:title>
   <news:publication_date>2026-04-27T05:36:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683905</loc>
  <lastmod>2026-04-27T05:35:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Exact Distributed Training: Random Forest with Billions of Examples（Exact Distributed Training: Random Forest with Billions of Examples）</news:title>
   <news:publication_date>2026-04-27T05:35:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683903</loc>
  <lastmod>2026-04-27T05:35:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ResNetは線形予測子より本当に優れているのか（Are ResNets Provably Better than Linear Predictors?）</news:title>
   <news:publication_date>2026-04-27T05:35:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683901</loc>
  <lastmod>2026-04-27T05:35:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Alquist: Alexa Prizeに挑んだオープンドメイン対話システム（Alquist: The Alexa Prize Socialbot）</news:title>
   <news:publication_date>2026-04-27T05:35:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683899</loc>
  <lastmod>2026-04-27T04:44:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>植物を“育てて形づくる”ロボット化—機械学習で実現するバイオハイブリッド制御（A Robot to Shape your Natural Plant: The Machine Learning Approach to Model and Control Bio-Hybrid Systems）</news:title>
   <news:publication_date>2026-04-27T04:44:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683897</loc>
  <lastmod>2026-04-27T04:44:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>助言付きグラフ探索問題の本質（The Graph Exploration Problem with Advice）</news:title>
   <news:publication_date>2026-04-27T04:44:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683895</loc>
  <lastmod>2026-04-27T04:43:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報量に基づく累積アブレーションによるニューラルネットワークと個々のニューロンの重要性の理解（Understanding Neural Networks and Individual Neuron Importance via Information-Ordered Cumulative Ablation）</news:title>
   <news:publication_date>2026-04-27T04:43:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683893</loc>
  <lastmod>2026-04-27T04:43:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ツイートの皮肉（アイロニー）検出を深掘りする（NTUA-SLP at SemEval-2018 Task 3: Tracking Ironic Tweets using Ensembles of Word and Character Level Attentive RNNs）</news:title>
   <news:publication_date>2026-04-27T04:43:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683891</loc>
  <lastmod>2026-04-27T04:43:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ的代謝フラックス解析が明かす細胞内フラックス結合（Bayesian Metabolic Flux Analysis reveals intracellular flux couplings）</news:title>
   <news:publication_date>2026-04-27T04:43:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683889</loc>
  <lastmod>2026-04-27T04:42:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆行アクティブラーニングによる乳がん画像分類の改善（Active Learning for Breast Cancer Identification）</news:title>
   <news:publication_date>2026-04-27T04:42:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683887</loc>
  <lastmod>2026-04-27T04:42:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ツイートの感情推定における深層注意RNNと転移学習の実践（NTUA-SLP at SemEval-2018 Task 1: Predicting Affective Content in Tweets with Deep Attentive RNNs and Transfer Learning）</news:title>
   <news:publication_date>2026-04-27T04:42:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683885</loc>
  <lastmod>2026-04-27T03:51:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ツイートから絵文字を予測する深層学習（Predicting Emojis using RNNs with Context-aware Attention）</news:title>
   <news:publication_date>2026-04-27T03:51:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683883</loc>
  <lastmod>2026-04-27T03:50:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔認識の深層学習総覧（Deep Face Recognition: A Survey）</news:title>
   <news:publication_date>2026-04-27T03:50:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683881</loc>
  <lastmod>2026-04-27T03:49:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Superframesによる動画の時間的セグメンテーション（Superframes, A Temporal Video Segmentation）</news:title>
   <news:publication_date>2026-04-27T03:49:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683879</loc>
  <lastmod>2026-04-27T03:49:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二層ニューラルネットワークの平均場視点（A Mean Field View of the Landscape of Two-Layer Neural Networks）</news:title>
   <news:publication_date>2026-04-27T03:49:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683877</loc>
  <lastmod>2026-04-27T03:48:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>投影線画から学ぶ3D形状のスタイル解析（Semi-Supervised Co-Analysis of 3D Shape Styles from Projected Lines）</news:title>
   <news:publication_date>2026-04-27T03:48:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683875</loc>
  <lastmod>2026-04-27T03:48:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボティクスにおける深層学習の限界と可能性（The Limits and Potentials of Deep Learning for Robotics）</news:title>
   <news:publication_date>2026-04-27T03:48:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683873</loc>
  <lastmod>2026-04-27T03:47:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックボックスモデルの特徴量重要度の可視化（Visualizing the Feature Importance for Black Box Models）</news:title>
   <news:publication_date>2026-04-27T03:47:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683871</loc>
  <lastmod>2026-04-27T02:55:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーケンス予測のための深層生成ネットワーク（Deep Generative Networks for Sequence Prediction）</news:title>
   <news:publication_date>2026-04-27T02:55:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683869</loc>
  <lastmod>2026-04-27T02:55:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワークを情報理論で理解する（Understanding Convolutional Neural Networks with Information Theory: An Initial Exploration）</news:title>
   <news:publication_date>2026-04-27T02:55:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683867</loc>
  <lastmod>2026-04-27T02:55:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アスペクト単位の感情判定を高精度にするAttention-over-Attention（Aspect Level Sentiment Classification with Attention-over-Attention Neural Networks）</news:title>
   <news:publication_date>2026-04-27T02:55:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683865</loc>
  <lastmod>2026-04-27T02:53:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>産業用故障診断のための深層転移ネットワーク（Deep Transfer Network with Joint Distribution Adaptation）</news:title>
   <news:publication_date>2026-04-27T02:53:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683863</loc>
  <lastmod>2026-04-27T02:53:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成データセット「Falling Things」による3D物体検出と姿勢推定（Falling Things: A Synthetic Dataset for 3D Object Detection and Pose Estimation）</news:title>
   <news:publication_date>2026-04-27T02:53:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683861</loc>
  <lastmod>2026-04-27T02:53:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層メキシコ湾のラグランジアン地理学（Lagrangian geography of the deep Gulf of Mexico）</news:title>
   <news:publication_date>2026-04-27T02:53:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683859</loc>
  <lastmod>2026-04-27T02:53:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Layered LearningによるMIRの階層的学習設計（Deep Layered Learning in MIR）</news:title>
   <news:publication_date>2026-04-27T02:53:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683857</loc>
  <lastmod>2026-04-27T02:01:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子少体系の基底状態をニューラルネットで求める方法（Method to solve quantum few-body problems with artificial neural networks）</news:title>
   <news:publication_date>2026-04-27T02:01:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683855</loc>
  <lastmod>2026-04-27T02:00:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非加法的利得を扱うオンライン経路学習の要点解説（Online Non-Additive Path Learning）</news:title>
   <news:publication_date>2026-04-27T02:00:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683853</loc>
  <lastmod>2026-04-27T02:00:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成データによる深層ネット訓練と現実ギャップの克服（Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomization）</news:title>
   <news:publication_date>2026-04-27T02:00:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683851</loc>
  <lastmod>2026-04-27T01:59:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所性を用いたスケーラブルな属性対応ネットワーク埋め込み（Scalable attribute-aware network embedding with locality）</news:title>
   <news:publication_date>2026-04-27T01:59:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683849</loc>
  <lastmod>2026-04-27T01:59:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重複する重みの再利用でCNNを効率化する手法（UCNN: Exploiting Computational Reuse in Deep Neural Networks via Weight Repetition）</news:title>
   <news:publication_date>2026-04-27T01:59:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683847</loc>
  <lastmod>2026-04-27T01:59:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人の教示とフィードバックによる対話学習（Dialogue Learning with Human Teaching and Feedback in End-to-End Trainable Task-Oriented Dialogue Systems）</news:title>
   <news:publication_date>2026-04-27T01:59:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683845</loc>
  <lastmod>2026-04-27T01:59:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速ウェイトとLSTMの融合が短期記憶を拡張する（FAST WEIGHT LONG SHORT-TERM MEMORY）</news:title>
   <news:publication_date>2026-04-27T01:59:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683843</loc>
  <lastmod>2026-04-27T01:07:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補完属性が示すゼロショット学習の新方向（Complementary Attributes: A New Clue to Zero-Shot Learning）</news:title>
   <news:publication_date>2026-04-27T01:07:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683841</loc>
  <lastmod>2026-04-27T01:05:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸制約最適化を二人ゲームで解く道（Two-Player Games for Efficient Non-Convex Constrained Optimization）</news:title>
   <news:publication_date>2026-04-27T01:05:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683839</loc>
  <lastmod>2026-04-27T01:05:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>堅牢性を学ぶ：深層多項式回帰（Learning how to be robust: Deep polynomial regression）</news:title>
   <news:publication_date>2026-04-27T01:05:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683837</loc>
  <lastmod>2026-04-27T01:04:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層マルチモーダル部分空間クラスタリングネットワーク（Deep Multimodal Subspace Clustering Networks）</news:title>
   <news:publication_date>2026-04-27T01:04:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683835</loc>
  <lastmod>2026-04-27T01:04:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガンマ線バースト宿主銀河の分子ガス質量の実測と解釈（Molecular gas masses of gamma-ray burst host galaxies）</news:title>
   <news:publication_date>2026-04-27T01:04:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683833</loc>
  <lastmod>2026-04-27T01:04:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学んだことを一度忘れさせる教え方：Adaptive Crowd Teaching with Exponentially Decayed Memory Learners（Unlearn What You Have Learned: Adaptive Crowd Teaching with Exponentially Decayed Memory Learners）</news:title>
   <news:publication_date>2026-04-27T01:04:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683831</loc>
  <lastmod>2026-04-27T01:03:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信号遅延とノードの不応期がネットワーク動態に与える影響（The Effect of Signaling Latencies and Node Refractory States on the Dynamics of Networks）</news:title>
   <news:publication_date>2026-04-27T01:03:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683829</loc>
  <lastmod>2026-04-27T00:11:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的事例で堅牢化する読解モデルの再訓練（Robust Machine Comprehension Models via Adversarial Training）</news:title>
   <news:publication_date>2026-04-27T00:11:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683827</loc>
  <lastmod>2026-04-27T00:10:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>政策勾配に対する内発的報酬の学習（Learning Intrinsic Rewards for Policy Gradient）</news:title>
   <news:publication_date>2026-04-27T00:10:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683825</loc>
  <lastmod>2026-04-27T00:10:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応クリッピングを導入したPPOの改良（An Adaptive Clipping Approach for Proximal Policy Optimization）</news:title>
   <news:publication_date>2026-04-27T00:10:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683823</loc>
  <lastmod>2026-04-27T00:10:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アルツハイマー言語特徴の検出とニューラルモデルの解釈（Detecting Linguistic Characteristics of Alzheimer’s Dementia by Interpreting Neural Models）</news:title>
   <news:publication_date>2026-04-27T00:10:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683821</loc>
  <lastmod>2026-04-27T00:09:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重要情報を同時に学習する要約学習（Multi-Reward Reinforced Summarization with Saliency and Entailment）</news:title>
   <news:publication_date>2026-04-27T00:09:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683819</loc>
  <lastmod>2026-04-27T00:09:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個人化ニューラル言語モデルによる実運用向けクエリ補完（Personalized neural language models for real-world query auto completion）</news:title>
   <news:publication_date>2026-04-27T00:09:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683817</loc>
  <lastmod>2026-04-27T00:09:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層確率的プログラミング言語の現状（Deep Probabilistic Programming Languages: A Qualitative Study）</news:title>
   <news:publication_date>2026-04-27T00:09:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683815</loc>
  <lastmod>2026-04-26T23:18:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト属性の削除・検索・生成による単純な感情・スタイル変換（Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer）</news:title>
   <news:publication_date>2026-04-26T23:18:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683813</loc>
  <lastmod>2026-04-26T23:17:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゆるく整列したデータからテキスト生成器を育てる手法（Bootstrapping Generators from Noisy Data）</news:title>
   <news:publication_date>2026-04-26T23:17:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683811</loc>
  <lastmod>2026-04-26T23:17:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層オブジェクト共同セグメンテーション (Deep Object Co-Segmentation)</news:title>
   <news:publication_date>2026-04-26T23:17:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683809</loc>
  <lastmod>2026-04-26T23:16:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タンパク質モデルの品質評価における深層トランスファー学習（Deep transfer learning in the assessment of the quality of protein models）</news:title>
   <news:publication_date>2026-04-26T23:16:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683807</loc>
  <lastmod>2026-04-26T23:15:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフに基づく選択的外れ値アンサンブル（Graph-based Selective Outlier Ensembles）</news:title>
   <news:publication_date>2026-04-26T23:15:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683805</loc>
  <lastmod>2026-04-26T23:15:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からのカラフルな3D復元（Im2Avatar: Colorful 3D Reconstruction from a Single Image）</news:title>
   <news:publication_date>2026-04-26T23:15:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683803</loc>
  <lastmod>2026-04-26T23:15:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人体解析のための深層生成モデル（DGPose: Deep Generative Models for Human Body Analysis）</news:title>
   <news:publication_date>2026-04-26T23:15:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683801</loc>
  <lastmod>2026-04-26T22:23:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>隣接行列の画像表現によるネットワーク署名（Network Signatures from Image Representation of Adjacency Matrices: Deep/Transfer Learning for Subgraph Classification）</news:title>
   <news:publication_date>2026-04-26T22:23:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683799</loc>
  <lastmod>2026-04-26T22:22:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PlaneNetによる単一画像からのピースワイズ平面復元（PlaneNet: Piece-wise Planar Reconstruction from a Single RGB Image）</news:title>
   <news:publication_date>2026-04-26T22:22:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683797</loc>
  <lastmod>2026-04-26T22:22:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音源分離評価のコミュニティ基盤化とデータ共有の前進（The 2018 Signal Separation Evaluation Campaign）</news:title>
   <news:publication_date>2026-04-26T22:22:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683795</loc>
  <lastmod>2026-04-26T22:21:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表とグラフの検出に向けた注目度ベースの畳み込みニューラルネットワーク（A Saliency-based Convolutional Neural Network for Table and Chart Detection in Digitized Documents）</news:title>
   <news:publication_date>2026-04-26T22:21:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683793</loc>
  <lastmod>2026-04-26T22:21:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転車の行動決定学習に関するDRLと高忠実度シミュレーションの枠組み（Automated Vehicle’s behavior decision making using deep reinforcement learning and high-fidelity simulation environment）</news:title>
   <news:publication_date>2026-04-26T22:21:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683791</loc>
  <lastmod>2026-04-26T22:20:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分モダリティから全モダリティ表現を作る技術の実務的意義（PM-GANs: Discriminative Representation Learning for Action Recognition Using Partial-modalities）</news:title>
   <news:publication_date>2026-04-26T22:20:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683789</loc>
  <lastmod>2026-04-26T22:20:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚追跡における時間的一貫性とグラフ最適化を用いたマニホールドランキング（Temporal Coherent and Graph Optimized Manifold Ranking for Visual Tracking）</news:title>
   <news:publication_date>2026-04-26T22:20:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683787</loc>
  <lastmod>2026-04-26T21:28:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力ごとに最適な専門家を選ぶ回帰のメタ学習（MetaBags: Bagged Meta-Decision Trees for Regression）</news:title>
   <news:publication_date>2026-04-26T21:28:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683785</loc>
  <lastmod>2026-04-26T21:20:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠損データを扱う階層的相関再構築（Hierarchical correlation reconstruction with missing data, for example for biology-inspired neuron）</news:title>
   <news:publication_date>2026-04-26T21:20:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683783</loc>
  <lastmod>2026-04-26T21:20:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自閉スペクトラム症監視における機械学習アルゴリズム比較（A Comparison of Machine Learning Algorithms for the Surveillance of Autism Spectrum Disorder）</news:title>
   <news:publication_date>2026-04-26T21:20:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683781</loc>
  <lastmod>2026-04-26T21:19:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層コピュラ情報ボトルネックによる疎な潜在表現学習（Learning Sparse Latent Representations with the Deep Copula Information Bottleneck）</news:title>
   <news:publication_date>2026-04-26T21:19:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683779</loc>
  <lastmod>2026-04-26T21:19:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関係学習におけるVC次元に基づく一般化境界（VC-Dimension Based Generalization Bounds for Relational Learning）</news:title>
   <news:publication_date>2026-04-26T21:19:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683777</loc>
  <lastmod>2026-04-26T21:19:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ARIELが解き明かす惑星形成の鍵（The contribution of the ARIEL space mission to the study of planetary formation）</news:title>
   <news:publication_date>2026-04-26T21:19:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683775</loc>
  <lastmod>2026-04-26T21:18:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LCMRによる推薦の共存メモリ設計（LCMR: Local and Centralized Memories for Collaborative Filtering with Unstructured Text）</news:title>
   <news:publication_date>2026-04-26T21:18:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683773</loc>
  <lastmod>2026-04-26T20:27:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速電波バーストと中性子星起源の可能性（Fast Radio Bursts and their Possible Neutron Star Origins）</news:title>
   <news:publication_date>2026-04-26T20:27:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683771</loc>
  <lastmod>2026-04-26T20:26:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サポート・テンソル・トレイン・マシン（A Support Tensor Train Machine）</news:title>
   <news:publication_date>2026-04-26T20:26:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683769</loc>
  <lastmod>2026-04-26T20:26:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>漸近的に正則なポリノミアル様写像のダイナミクス（DYNAMICS OF ASYMPTOTICALLY HOLOMORPHIC POLYNOMIAL-LIKE MAPS）</news:title>
   <news:publication_date>2026-04-26T20:26:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683767</loc>
  <lastmod>2026-04-26T20:25:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースな教師なしカプセルが示す一般化性能の向上（Sparse Unsupervised Capsules Generalize Better）</news:title>
   <news:publication_date>2026-04-26T20:25:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683765</loc>
  <lastmod>2026-04-26T20:25:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数カーネル行列の欠損補完をパラメータ化で安定化する手法（Parametric Models for Mutual Kernel Matrix Completion）</news:title>
   <news:publication_date>2026-04-26T20:25:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683763</loc>
  <lastmod>2026-04-26T20:25:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ上の特徴伝播の新視点（Feature Propagation on Graph: A New Perspective to Graph Representation Learning）</news:title>
   <news:publication_date>2026-04-26T20:25:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683761</loc>
  <lastmod>2026-04-26T20:25:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Raﬁki: 機械学習を分析サービスとして提供するシステム（Raﬁki: Machine Learning as an Analytics Service System）</news:title>
   <news:publication_date>2026-04-26T20:25:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683759</loc>
  <lastmod>2026-04-26T19:33:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期的文脈を符号化する多重時間スケール予測符号化モデル（Encoding Longer-term Contextual Multi-modal Information in a Predictive Coding Model）</news:title>
   <news:publication_date>2026-04-26T19:33:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683757</loc>
  <lastmod>2026-04-26T19:32:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>円柱周りの非定常流のデータ駆動予測（Data-driven prediction of unsteady flow over a circular cylinder using deep learning）</news:title>
   <news:publication_date>2026-04-26T19:32:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683755</loc>
  <lastmod>2026-04-26T19:32:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重力波と銀河クラスタリングで測るハッブル定数（Measuring the Hubble constant: gravitational wave observations meet galaxy clustering）</news:title>
   <news:publication_date>2026-04-26T19:32:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683753</loc>
  <lastmod>2026-04-26T19:31:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模分散型科学ワークフローの運用データに対する深層学習の適用（Deep Learning on Operational Facility Data Related to Large-Scale Distributed Area Scientific Workflows）</news:title>
   <news:publication_date>2026-04-26T19:31:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683751</loc>
  <lastmod>2026-04-26T19:31:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3次元柔軟ビンパッキング問題を解くマルチタスクSelected Learning手法（A Multi-task Selected Learning Approach for Solving 3D Flexible Bin Packing Problem）</news:title>
   <news:publication_date>2026-04-26T19:31:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683749</loc>
  <lastmod>2026-04-26T19:31:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>順序認識によるトリプレット再重み付けで改善する深層バイナリエンベッディングネットワーク（Improving Deep Binary Embedding Networks by Order-aware Reweighting of Triplets）</news:title>
   <news:publication_date>2026-04-26T19:31:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683747</loc>
  <lastmod>2026-04-26T19:31:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェブ動画から良質な学習例を選ぶためのマルチモーダル共学習（Multimodal Co-Training for Selecting Good Examples from Webly Labeled Video）</news:title>
   <news:publication_date>2026-04-26T19:31:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683745</loc>
  <lastmod>2026-04-26T18:39:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインマーケットプレイスにおける出品者詐欺検出（Detection of Fraudulent Sellers in Online Marketplaces using Support Vector Machine Approach）</news:title>
   <news:publication_date>2026-04-26T18:39:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683743</loc>
  <lastmod>2026-04-26T18:39:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>骨格データからの共起特徴学習による動作認識と検出の階層的集約（Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation）</news:title>
   <news:publication_date>2026-04-26T18:39:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683741</loc>
  <lastmod>2026-04-26T18:38:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復残差型画像デコンボリューション（Iterative Residual Image Deconvolution）</news:title>
   <news:publication_date>2026-04-26T18:38:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683739</loc>
  <lastmod>2026-04-26T18:37:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的にランクを決めるFactorization Machineの強化（A Boosting Framework of Factorization Machine）</news:title>
   <news:publication_date>2026-04-26T18:37:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683737</loc>
  <lastmod>2026-04-26T18:37:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一視点からの3D形状予測に関する表面表現とボリューム表現の比較（Pixels, voxels, and views: A study of shape representations for single view 3D object shape prediction）</news:title>
   <news:publication_date>2026-04-26T18:37:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683735</loc>
  <lastmod>2026-04-26T18:37:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ListOps: 潜在木構造学習を診断するためのデータセット（ListOps: A Diagnostic Dataset for Latent Tree Learning）</news:title>
   <news:publication_date>2026-04-26T18:37:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683733</loc>
  <lastmod>2026-04-26T18:36:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化型コートレーニング（Reinforced Co-Training）</news:title>
   <news:publication_date>2026-04-26T18:36:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683731</loc>
  <lastmod>2026-04-26T17:45:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語から学ぶ自動着色（Learning to Color from Language）</news:title>
   <news:publication_date>2026-04-26T17:45:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683729</loc>
  <lastmod>2026-04-26T17:45:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの新規視点合成に対する幾何認識型ディープネットワーク（Geometry-aware Deep Network for Single-Image Novel View Synthesis）</news:title>
   <news:publication_date>2026-04-26T17:45:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683727</loc>
  <lastmod>2026-04-26T17:45:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルフリー線形二次制御の専門家予測への帰着（Model-Free Linear Quadratic Control via Reduction to Expert Prediction）</news:title>
   <news:publication_date>2026-04-26T17:45:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683725</loc>
  <lastmod>2026-04-26T17:44:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファッション領域における注意付き知識蒸留による互換性モデリング（Neural Compatibility Modeling with Attentive Knowledge Distillation）</news:title>
   <news:publication_date>2026-04-26T17:44:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683723</loc>
  <lastmod>2026-04-26T17:44:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DPRedによる典型的な活性化値と重みを重視する手法（DPRed: Making Typical Activation and Weight Values Matter In Deep Learning Computing）</news:title>
   <news:publication_date>2026-04-26T17:44:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683721</loc>
  <lastmod>2026-04-26T17:44:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数データセットから学ぶ意味解析の共同学習（Learning Joint Semantic Parsers from Disjoint Data）</news:title>
   <news:publication_date>2026-04-26T17:44:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683719</loc>
  <lastmod>2026-04-26T17:43:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一変量のAUC上界（A Univariate Bound of Area Under ROC）</news:title>
   <news:publication_date>2026-04-26T17:43:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683717</loc>
  <lastmod>2026-04-26T16:53:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>活性化の大きさを制約するニューラルネットの正則化（MaxGain: Regularisation of Neural Networks by Constraining Activation Magnitudes）</news:title>
   <news:publication_date>2026-04-26T16:53:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683715</loc>
  <lastmod>2026-04-26T16:52:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザーフィードバックでNMTは実用的に改善できるか（Can Neural Machine Translation be Improved with User Feedback?）</news:title>
   <news:publication_date>2026-04-26T16:52:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683713</loc>
  <lastmod>2026-04-26T16:52:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑ネットワークの超球面空間における機械学習解析（MACHINE LEARNING ANALYSIS OF COMPLEX NETWORKS IN HYPERSPHERICAL SPACE）</news:title>
   <news:publication_date>2026-04-26T16:52:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683711</loc>
  <lastmod>2026-04-26T16:51:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>数学とは何かの本質を問う（What is Math Really?）</news:title>
   <news:publication_date>2026-04-26T16:51:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683709</loc>
  <lastmod>2026-04-26T16:51:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リスク感受性強化学習のための状態拡張変換（State-Augmentation Transformations for Risk-Sensitive Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-26T16:51:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683707</loc>
  <lastmod>2026-04-26T16:51:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床写真における疾患皮膚と健常皮膚のセグメンテーション（Segmentation of both Diseased and Healthy Skin from Clinical Photographs in a Primary Care Setting）</news:title>
   <news:publication_date>2026-04-26T16:51:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683705</loc>
  <lastmod>2026-04-26T16:51:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>神経ネットワークによる英文文法誤り訂正を低リソース機械翻訳として捉える（Approaching Neural Grammatical Error Correction as a Low-Resource Machine Translation Task）</news:title>
   <news:publication_date>2026-04-26T16:51:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683703</loc>
  <lastmod>2026-04-26T16:00:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UCBoost: 低計算コストで近似最適を実現するバンディット強化法（UCBoost: A Boosting Approach to Tame Complexity and Optimality for Stochastic Bandits）</news:title>
   <news:publication_date>2026-04-26T16:00:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683701</loc>
  <lastmod>2026-04-26T16:00:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>六方最密構造材料における応力ホットスポット予測（Applied Machine Learning to Predict Stress Hotspots II: Hexagonal close packed materials）</news:title>
   <news:publication_date>2026-04-26T16:00:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683699</loc>
  <lastmod>2026-04-26T16:00:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Defo-Netによる物体変形予測（Defo-Net: Learning Body Deformation using Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-04-26T16:00:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683697</loc>
  <lastmod>2026-04-26T15:59:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M-PACT：再現可能な行動分類研究のためのオープンソースプラットフォーム（M-PACT: An Open Source Platform for Repeatable Activity Classification Research）</news:title>
   <news:publication_date>2026-04-26T15:59:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683695</loc>
  <lastmod>2026-04-26T15:59:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>活動小惑星311Pの核とその回転性（The Nucleus of Active Asteroid 311P/(2013 P5) PANSTARRS）</news:title>
   <news:publication_date>2026-04-26T15:59:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683693</loc>
  <lastmod>2026-04-26T15:59:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次密結合残差ネットワークによる単一フレーム画像超解像（Densely Connected High Order Residual Network for Single Frame Image Super Resolution）</news:title>
   <news:publication_date>2026-04-26T15:59:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683691</loc>
  <lastmod>2026-04-26T15:59:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間を組み込んだ反復型機械学習の高速化（Accelerating Human-in-the-loop Machine Learning: Challenges and Opportunities）</news:title>
   <news:publication_date>2026-04-26T15:59:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683689</loc>
  <lastmod>2026-04-26T15:08:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮サイズで見るニューラルネットの一般化（Non-vacuous generalization bounds at the ImageNet scale: A PAC-Bayesian compression approach）</news:title>
   <news:publication_date>2026-04-26T15:08:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683687</loc>
  <lastmod>2026-04-26T15:07:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホリスティック分光法：フォトニックコームによる広視野多光子分光イメージの完全再構成（Holistic spectroscopy: Complete reconstruction of a wide-field, multi-object spectroscopic image using a photonic comb）</news:title>
   <news:publication_date>2026-04-26T15:07:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683685</loc>
  <lastmod>2026-04-26T15:07:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FPGA上での深層ニューラルネットワークの高速推論（Fast inference of deep neural networks in FPGAs for particle physics）</news:title>
   <news:publication_date>2026-04-26T15:07:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683683</loc>
  <lastmod>2026-04-26T15:06:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>恒常性可塑性と臨界性における全脳モデルでの機能ネットワークの出現（Homeostatic plasticity and emergence of functional networks in a whole-brain model at criticality）</news:title>
   <news:publication_date>2026-04-26T15:06:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683681</loc>
  <lastmod>2026-04-26T15:05:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二重チャネル整合ネットワークによる教師なしシーン適応（Dual Channel-wise Alignment Networks for Unsupervised Scene Adaptation）</news:title>
   <news:publication_date>2026-04-26T15:05:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683679</loc>
  <lastmod>2026-04-26T15:04:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人の口頭指示を強化学習に組み込む新しい手法（Newtonian Action Advice: Integrating Human Verbal Instruction with Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-26T15:04:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/683677</loc>
  <lastmod>2026-04-26T15:04:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間変化するネットワークの潜在表現を学ぶモデル（Models for Capturing Temporal Smoothness in Evolving Networks for Learning Latent Representation of Nodes）</news:title>
   <news:publication_date>2026-04-26T15:04:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
</urlset>
