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   <news:title>地震位相の結びつけを深層学習で行うPhaseLink（PhaseLink: A Deep Learning Approach to Seismic Phase Association）</news:title>
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   <news:title>コスト感度を取り入れた能動学習による頭部CT出血検出（Cost-Sensitive Active Learning for Intracranial Hemorrhage Detection）</news:title>
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   <news:title>リアルタイム偽装顔認識のための教師あり学習手法（A Supervised Learning Methodology for Real-Time Disguised Face Recognition in the Wild）</news:title>
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   <news:title>トラッケルト協調による教師なし人物再識別（Unsupervised Person Re-identification by Deep Learning Tracklet Association）</news:title>
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   <news:title>攻撃が“転移”する理由 ― 侵入と毒殺攻撃の伝播性の解明（Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks）</news:title>
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   <news:title>能動的逐次学習者の機械教授（Machine Teaching of Active Sequential Learners）</news:title>
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    <news:language>ja</news:language>
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   <news:title>オンライン適応法、普遍性と加速（Online Adaptive Methods, Universality and Acceleration）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>構造的に相互作用するElastic Netによる最も情報量の多い特徴抽出（Identifying The Most Informative Features Using A Structurally Interacting Elastic Net）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>PMUデータを用いたリアルタイム過渡安定性評価へのEOS-ELMとBinary Jaya特徴選択の適用（Application of EOS-ELM with Binary Jaya-Based Feature Selection to Real-Time Transient Stability Assessment Using PMU Data）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ELMと改良アントマイナーによる過渡安定性評価のルール抽出（Rule Extraction Based on Extreme Learning Machine and an Improved Ant-Miner Algorithm for Transient Stability Assessment）</news:title>
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    <news:language>ja</news:language>
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   <news:title>道路品質情報を組み込む動的経路計画（iDriveSense: Dynamic Route Planning Involving Roads Quality Information）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>近傍法で解釈するニューラルネットワーク（Interpreting Neural Networks With Nearest Neighbors）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>計測率可変型ニューラルネットワークによる空間マルチプレクサ（Rate-Adaptive Neural Networks for Spatial Multiplexers）</news:title>
   <news:publication_date>2026-06-11T07:24:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-11T07:23:42Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>インターネット動画から学ぶスポーツ用カメラ選択（Learning Sports Camera Selection from Internet Videos）</news:title>
   <news:publication_date>2026-06-11T07:23:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699421</loc>
  <lastmod>2026-06-11T06:32:34Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>マルチGPU環境におけるモデル並列化による効率的かつ頑健なDNN訓練（Efficient and Robust Parallel DNN Training through Model Parallelism on Multi-GPU Platform）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-11T06:32:19Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>タイプIIケフェイドにおける多様な力学現象（Diversity of dynamical phenomena in type II Cepheids of the OGLE collection）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-11T06:31:55Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ニューラル誘導制約論理プログラミングによるプログラム合成（Neural Guided Constraint Logic Programming for Program Synthesis）</news:title>
   <news:publication_date>2026-06-11T06:31:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-11T06:31:36Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>オンラインニュースにおける利用者反応のマルチラベル分類（Multi-label Classification of User Reactions in Online News）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-11T06:31:27Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>非パラメトリック変分推論とグラフ畳み込みによるガウス過程（Non-Parametric Variational Inference with Graph Convolutional Networks for Gaussian Processes）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-11T06:31:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ニュース記事から都市間の意味的関連性を抽出する方法（Extracting and Analyzing Semantic Relatedness between Cities Using News Articles）</news:title>
   <news:publication_date>2026-06-11T06:31:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699409</loc>
  <lastmod>2026-06-11T06:31:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Context-Free Transductions with Neural Stacks（Context-Free Transductions with Neural Stacks）</news:title>
   <news:publication_date>2026-06-11T06:31:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699407</loc>
  <lastmod>2026-06-11T05:39:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ビルクホフダイヤモンドの二重役割（The Birkhoff Diamond as Double Agent）</news:title>
   <news:publication_date>2026-06-11T05:39:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-11T05:39:30Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>映像に映る煙を深層顕著性で検出する（Video Smoke Detection Based on Deep Saliency Network）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-11T05:39:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>モデル再利用による概念ドリフトの扱い（Handling Concept Drift via Model Reuse）</news:title>
   <news:publication_date>2026-06-11T05:39:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-11T05:38:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>境界指標を用いた注目型意味役割付与（Attentive Semantic Role Labeling with Boundary Indicator）</news:title>
   <news:publication_date>2026-06-11T05:38:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-11T05:38:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>テキスト理解のための明示的文脈セマンティクス（Explicit Contextual Semantics for Text Comprehension）</news:title>
   <news:publication_date>2026-06-11T05:38:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-11T05:37:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>UAVによる地形モニタリング向け情報指向経路計画フレームワーク（An informative path planning framework for UAV-based terrain monitoring）</news:title>
   <news:publication_date>2026-06-11T05:37:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-11T05:37:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ネットワーク埋め込みに対する高速勾配攻撃（Fast Gradient Attack on Network Embedding）</news:title>
   <news:publication_date>2026-06-11T05:37:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699393</loc>
  <lastmod>2026-06-11T04:46:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造を保つ変換による多様で転送可能な敵対的例の生成（Structure-Preserving Transformation: Generating Diverse and Transferable Adversarial Examples）</news:title>
   <news:publication_date>2026-06-11T04:46:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699391</loc>
  <lastmod>2026-06-11T04:46:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像鑑識のための敵対的学習とAtrous畳み込みを用いた深度マッチング（Adversarial Learning for Image Forensics Deep Matching with Atrous Convolution）</news:title>
   <news:publication_date>2026-06-11T04:46:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/699389</loc>
  <lastmod>2026-06-11T04:45:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンスベースの深層転移学習（Instance-based Deep Transfer Learning）</news:title>
   <news:publication_date>2026-06-11T04:45:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/699387</loc>
  <lastmod>2026-06-11T04:44:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒューマン・イン・ザ・ループにおける“弱い制御”の提案（“Weak” Control for Human-in-the-loop Systems）</news:title>
   <news:publication_date>2026-06-11T04:44:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/699385</loc>
  <lastmod>2026-06-11T04:44:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>アキレス腱断裂のリハビリ予後を同時に補完と予測する確率的手法（Simultaneous Measurement Imputation and Outcome Prediction for Achilles Tendon Rupture Rehabilitation）</news:title>
   <news:publication_date>2026-06-11T04:44:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-11T04:44:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>画像で説明できる単語表現の探求（Exploration on Grounded Word Embedding: Matching Words and Images with Image-Enhanced Skip-Gram Model）</news:title>
   <news:publication_date>2026-06-11T04:44:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-11T04:43:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合統計推定法による相互情報量推定と情報流の解析（Hybrid Statistical Estimation of Mutual Information and its Application to Information Flow）</news:title>
   <news:publication_date>2026-06-11T04:43:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699379</loc>
  <lastmod>2026-06-11T03:52:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超高輝度超新星 SN 2015bn のX線非検出が示す「失われたエネルギー」問題（Where is the engine hiding its missing energy?）</news:title>
   <news:publication_date>2026-06-11T03:52:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699377</loc>
  <lastmod>2026-06-11T03:52:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音響反響を取り除き音声認証を強化する二重ラベル深層LSTM（Dual-label Deep LSTM Dereverberation for Speaker Verification）</news:title>
   <news:publication_date>2026-06-11T03:52:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699375</loc>
  <lastmod>2026-06-11T03:51:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>千日間のSN 2015bnが示すマグネター駆動の兆候（One thousand days of SN 2015bn: HST imaging shows a light curve flattening consistent with magnetar predictions）</news:title>
   <news:publication_date>2026-06-11T03:51:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699373</loc>
  <lastmod>2026-06-11T03:50:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子ハイパーグラフ文法による分子最適化（Molecular Hypergraph Grammar with Its Application to Molecular Optimization）</news:title>
   <news:publication_date>2026-06-11T03:50:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699371</loc>
  <lastmod>2026-06-11T03:50:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネステッド・ダイコトミーの較正が大規模多クラスで果たす役割（On the Calibration of Nested Dichotomies for Large Multiclass Tasks）</news:title>
   <news:publication_date>2026-06-11T03:50:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699369</loc>
  <lastmod>2026-06-11T03:50:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの実世界点群生成（RealPoint3D: Point Cloud Generation from a Single Image with Complex Background）</news:title>
   <news:publication_date>2026-06-11T03:50:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699367</loc>
  <lastmod>2026-06-11T03:49:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RF駆動アンビエントバックキャッターの動的スペクトラム利用とオンライン強化学習（Optimal and Low-Complexity Dynamic Spectrum Access for RF-Powered Ambient Backscatter System with Online Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-11T03:49:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699365</loc>
  <lastmod>2026-06-11T02:58:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入れ子二分法アンサンブルの複数部分集合評価（Ensembles of Nested Dichotomies with Multiple Subset Evaluation）</news:title>
   <news:publication_date>2026-06-11T02:58:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699363</loc>
  <lastmod>2026-06-11T02:58:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習型画像圧縮における自己回帰と階層的事前分布の併用による飛躍的改善（Joint Autoregressive and Hierarchical Priors for Learned Image Compression）</news:title>
   <news:publication_date>2026-06-11T02:58:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699361</loc>
  <lastmod>2026-06-11T02:57:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可逆（Invertible）なデコーダを利用した教師なし文表現学習（Exploiting Invertible Decoders for Unsupervised Sentence Representation Learning）</news:title>
   <news:publication_date>2026-06-11T02:57:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699359</loc>
  <lastmod>2026-06-11T02:57:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークによる電子密度とエネルギーの高速予測（Deep Neural Network Computes Electron Densities and Energies of a Large Set of Organic Molecules Faster than Density Functional Theory）</news:title>
   <news:publication_date>2026-06-11T02:57:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699357</loc>
  <lastmod>2026-06-11T02:56:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習でNP完全問題を解く：決定版TSPのためのグラフニューラルネットワーク (Learning to Solve NP-Complete Problems: A Graph Neural Network for Decision TSP)</news:title>
   <news:publication_date>2026-06-11T02:56:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699355</loc>
  <lastmod>2026-06-11T02:56:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散環境での差分プライバシー付き置換なし確率的勾配降下法（Decentralized Differentially Private Without-Replacement Stochastic Gradient Descent）</news:title>
   <news:publication_date>2026-06-11T02:56:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699353</loc>
  <lastmod>2026-06-11T02:55:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Coupled IGMM-GANsによる深層多峰性異常検知（Coupled IGMM-GANs for deep multimodal anomaly detection in human mobility data）</news:title>
   <news:publication_date>2026-06-11T02:55:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699351</loc>
  <lastmod>2026-06-11T02:05:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DensSiamが変えたトラッキングの常識 — 密結合と自己注意で精度と速度を両立する （DensSiam: End-to-End Densely-Siamese Network with Self-Attention Model for Object Tracking）</news:title>
   <news:publication_date>2026-06-11T02:05:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699349</loc>
  <lastmod>2026-06-11T02:04:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模行動集合グラフ上のバンディット（BLAG: Bandit on Large Action Set Graph）</news:title>
   <news:publication_date>2026-06-11T02:04:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699347</loc>
  <lastmod>2026-06-11T02:04:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフニューラルネットワークにおける辺特徴の活用（Exploiting Edge Features in Graph Neural Networks）</news:title>
   <news:publication_date>2026-06-11T02:04:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699345</loc>
  <lastmod>2026-06-11T02:03:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的に発火するアームを伴う組合せ多腕バンディットに対するThompson Samplingの解析（Thompson Sampling for Combinatorial Multi-armed Bandit with Probabilistically Triggered Arms）</news:title>
   <news:publication_date>2026-06-11T02:03:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699343</loc>
  <lastmod>2026-06-11T02:03:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>移住をサブモジュラー最適化として扱う（Migration as Submodular Optimization）</news:title>
   <news:publication_date>2026-06-11T02:03:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699341</loc>
  <lastmod>2026-06-11T02:03:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイム学習者成績予測とドメイン適応（GritNet 2: Real-Time Student Performance Prediction with Domain Adaptation）</news:title>
   <news:publication_date>2026-06-11T02:03:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699339</loc>
  <lastmod>2026-06-11T02:02:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トピック一貫性を訓練目標に組み込む手法（Coherence-Aware Neural Topic Modeling）</news:title>
   <news:publication_date>2026-06-11T02:02:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699337</loc>
  <lastmod>2026-06-11T01:11:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ類似度評価を変える手法：Return Probabilityに基づくGraph Kernel（RetGK: Graph Kernels based on Return Probabilities of Random Walks）</news:title>
   <news:publication_date>2026-06-11T01:11:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699335</loc>
  <lastmod>2026-06-11T01:11:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的グラフ埋め込みでネットワークの時間変化をつかむ（dyngraph2vec: Capturing Network Dynamics using Dynamic Graph Representation Learning）</news:title>
   <news:publication_date>2026-06-11T01:11:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699333</loc>
  <lastmod>2026-06-11T01:11:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>認知資源の動的モデルが示すテスト中のパフォーマンス変化（Model of Cognitive Dynamics Predicts Performance on Standardized Tests）</news:title>
   <news:publication_date>2026-06-11T01:11:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699331</loc>
  <lastmod>2026-06-11T01:10:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし文章圧縮：ノイズ除去オートエンコーダによるアプローチ (Unsupervised Sentence Compression using Denoising Auto-Encoders)</news:title>
   <news:publication_date>2026-06-11T01:10:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699329</loc>
  <lastmod>2026-06-11T01:10:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>参照画像による検証を伴う分類（Are You Sure You Want To Do That? Classification with Verification）</news:title>
   <news:publication_date>2026-06-11T01:10:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699327</loc>
  <lastmod>2026-06-11T01:10:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移学習可能なデータベース向け自然言語インタフェース（A Transfer-Learnable Natural Language Interface for Databases）</news:title>
   <news:publication_date>2026-06-11T01:10:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699325</loc>
  <lastmod>2026-06-11T01:09:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様な質問のニューラル生成（Neural Generation of Diverse Questions using Answer Focus, Contextual and Linguistic Features）</news:title>
   <news:publication_date>2026-06-11T01:09:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699323</loc>
  <lastmod>2026-06-11T00:19:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Unityを用いた汎用的知能エージェントプラットフォーム（Unity: A General Platform for Intelligent Agents）</news:title>
   <news:publication_date>2026-06-11T00:19:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699321</loc>
  <lastmod>2026-06-11T00:18:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味的に妥当なグラフの制約付き生成を実現する正則化VAE（Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders）</news:title>
   <news:publication_date>2026-06-11T00:18:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699319</loc>
  <lastmod>2026-06-11T00:18:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非同次線形偏微分方程式のための量子アルゴリズム（Quantum algorithm for non-homogeneous linear partial differential equations）</news:title>
   <news:publication_date>2026-06-11T00:18:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699317</loc>
  <lastmod>2026-06-11T00:17:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡データに対する変分オーバーサンプリング（VOS: a Method for Variational Oversampling of Imbalanced Data）</news:title>
   <news:publication_date>2026-06-11T00:17:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699315</loc>
  <lastmod>2026-06-11T00:17:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SECS: 環境に応じたクラススキューで効率化する深層ストリーム処理（SECS: Efficient Deep Stream Processing via Class Skew Dichotomy）</news:title>
   <news:publication_date>2026-06-11T00:17:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699313</loc>
  <lastmod>2026-06-11T00:17:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>訓練セット中心点の原理的構成と確率的サンプリングによる最近傍分類精度の向上 (Improving the accuracy of nearest-neighbor classification using principled construction and stochastic sampling of training-set centroids)</news:title>
   <news:publication_date>2026-06-11T00:17:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699311</loc>
  <lastmod>2026-06-11T00:16:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間ボトルネックによる畳み込み高速化（Accelerating Deep Neural Networks with Spatial Bottleneck Modules）</news:title>
   <news:publication_date>2026-06-11T00:16:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699309</loc>
  <lastmod>2026-06-10T23:25:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表意文字のサブワードモデル（LOGOGRAPHIC SUBWORD MODEL FOR NEURAL MACHINE TRANSLATION）</news:title>
   <news:publication_date>2026-06-10T23:25:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699307</loc>
  <lastmod>2026-06-10T23:25:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>方策の不変量学習による汎化（Learning Invariances for Policy Generalization）</news:title>
   <news:publication_date>2026-06-10T23:25:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699305</loc>
  <lastmod>2026-06-10T23:24:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HyperGCN：ハイパーグラフ上でのGCN学習手法（HyperGCN: A New Method of Training Graph Convolutional Networks on Hypergraphs）</news:title>
   <news:publication_date>2026-06-10T23:24:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699303</loc>
  <lastmod>2026-06-10T23:24:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>360度映像のための自己教師あり空間音声生成（Self-Supervised Generation of Spatial Audio for 360◦Video）</news:title>
   <news:publication_date>2026-06-10T23:24:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699301</loc>
  <lastmod>2026-06-10T23:24:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SENetと半教師あり学習のアンサンブルによる皮膚病変分類（Skin lesion classification with ensemble of squeeze-and-excitation networks and semi-supervised learning）</news:title>
   <news:publication_date>2026-06-10T23:24:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699299</loc>
  <lastmod>2026-06-10T23:23:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NV中心を用いたnano-NMRと深層学習による雑音克服（NV center based nano-NMR enhanced by deep learning）</news:title>
   <news:publication_date>2026-06-10T23:23:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699297</loc>
  <lastmod>2026-06-10T23:23:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D形状分類器の深掘り（A Deeper Look at 3D Shape Classifiers）</news:title>
   <news:publication_date>2026-06-10T23:23:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699295</loc>
  <lastmod>2026-06-10T22:32:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層仮説検定による異種ネットワーク母集団の比較（Multi-level hypothesis testing for populations of heterogeneous networks）</news:title>
   <news:publication_date>2026-06-10T22:32:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699293</loc>
  <lastmod>2026-06-10T22:24:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トーリック多様体上の射影束コホモロジーを機械学習で解析する（Machine Learning Line Bundle Cohomologies of Hypersurfaces in Toric Varieties）</news:title>
   <news:publication_date>2026-06-10T22:24:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699291</loc>
  <lastmod>2026-06-10T22:24:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列平均化の誤差を再考する（Revisiting Inaccuracies of Time Series Averaging under Dynamic Time Warping）</news:title>
   <news:publication_date>2026-06-10T22:24:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699289</loc>
  <lastmod>2026-06-10T22:24:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の概念知識を模倣する疎（スパース）マルチモーダル埋め込み（Using sparse semantic embeddings learned from multimodal text and image data to model human conceptual knowledge）</news:title>
   <news:publication_date>2026-06-10T22:24:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699287</loc>
  <lastmod>2026-06-10T22:23:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推薦システムにおける行動条件付き系列モデリング（Action-conditional Sequence Modeling for Recommendation）</news:title>
   <news:publication_date>2026-06-10T22:23:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699285</loc>
  <lastmod>2026-06-10T22:23:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果的公平性モデルによるバイアスデータの学習（Fairness through Causal Awareness: Learning Causal Latent-Variable Models for Biased Data）</news:title>
   <news:publication_date>2026-06-10T22:23:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699283</loc>
  <lastmod>2026-06-10T22:22:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MixUpの外部マニフェールド局所線形正則化としての解釈 (MixUp as Locally Linear Out-Of-Manifold Regularization)</news:title>
   <news:publication_date>2026-06-10T22:22:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699281</loc>
  <lastmod>2026-06-10T21:31:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースカーネルPCAによる外れ値検知（Sparse Kernel PCA for Outlier Detection）</news:title>
   <news:publication_date>2026-06-10T21:31:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699279</loc>
  <lastmod>2026-06-10T21:30:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FI-GRL: 投影コスト保存による高速帰納的グラフ表現学習（FI-GRL: Fast Inductive Graph Representation Learning via Projection-Cost Preservation）</news:title>
   <news:publication_date>2026-06-10T21:30:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699277</loc>
  <lastmod>2026-06-10T21:30:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様体として読む都市データの解像度（Manifold Cities: Social variables of urban areas in the UK）</news:title>
   <news:publication_date>2026-06-10T21:30:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699275</loc>
  <lastmod>2026-06-10T21:30:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>StackNetによる継続学習の設計（StackNet: Stacking feature maps for Continual learning）</news:title>
   <news:publication_date>2026-06-10T21:30:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699273</loc>
  <lastmod>2026-06-10T21:30:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BiasedWalkによるグラフ表現学習の新展開（BiasedWalk: Biased Sampling for Representation Learning on Graphs）</news:title>
   <news:publication_date>2026-06-10T21:30:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699271</loc>
  <lastmod>2026-06-10T21:29:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタモルフィック関係に基づく敵対的攻撃と微分可能ニューラルコンピュータ（Metamorphic Relation Based Adversarial Attacks on Differentiable Neural Computer）</news:title>
   <news:publication_date>2026-06-10T21:29:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699269</loc>
  <lastmod>2026-06-10T21:29:29Z</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によるテキスト分類とオープンドメイン質問応答への応用（Convolutional Neural Network: Text Classification Model for Open Domain Question Answering System）</news:title>
   <news:publication_date>2026-06-10T21:29:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699267</loc>
  <lastmod>2026-06-10T20:38:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳活動と一致する深層ビデオ表現の最適化 (Optimizing deep video representation to match brain activity)</news:title>
   <news:publication_date>2026-06-10T20:38:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699265</loc>
  <lastmod>2026-06-10T20:38:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>符号付きソーシャルネットワークにおけるノード分類と拡散界面法（Node Classification for Signed Social Networks Using Diffuse Interface Methods）</news:title>
   <news:publication_date>2026-06-10T20:38:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699263</loc>
  <lastmod>2026-06-10T20:37:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果推論の入門—データサイエンスにおける因果の道筋（A Primer on Causality in Data Science）</news:title>
   <news:publication_date>2026-06-10T20:37:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699261</loc>
  <lastmod>2026-06-10T20:37:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別時系列予測に挑むDeep Recurrent Survival Analysis（Deep Recurrent Survival Analysis）</news:title>
   <news:publication_date>2026-06-10T20:37:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699259</loc>
  <lastmod>2026-06-10T20:36:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所的な敵対的入力の検出と人間可解釈な防御（Detecting Potential Local Adversarial Examples for Human-Interpretable Defense）</news:title>
   <news:publication_date>2026-06-10T20:36:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699257</loc>
  <lastmod>2026-06-10T20:36:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチネットワークトポロジーの深層特徴学習（Deep Feature Learning of Multi-Network Topology for Node Classification）</news:title>
   <news:publication_date>2026-06-10T20:36:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699255</loc>
  <lastmod>2026-06-10T20:36:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回答分離によるニューラル質問生成の改善（Improving Neural Question Generation using Answer Separation）</news:title>
   <news:publication_date>2026-06-10T20:36:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699253</loc>
  <lastmod>2026-06-10T19:45:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視点を切り替えて学ぶ直観的物理予測（Neural Allocentric Intuitive Physics Prediction from Real Videos）</news:title>
   <news:publication_date>2026-06-10T19:45:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699251</loc>
  <lastmod>2026-06-10T19:44:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>訓練されたフィードバックネットワークにおける大域的安定性の幾何学的解析（A geometrical analysis of global stability in trained feedback networks）</news:title>
   <news:publication_date>2026-06-10T19:44:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699249</loc>
  <lastmod>2026-06-10T19:44:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>過去報酬統計を活用したオンポリシー学習の改善（Improving On-policy Learning with Statistical Reward Accumulation）</news:title>
   <news:publication_date>2026-06-10T19:44:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699247</loc>
  <lastmod>2026-06-10T19:43:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続稼働タスク向けにシミュレーション期間を可変化したモンテカルロ木探索（Monte Carlo Tree Search with Scalable Simulation Periods for Continuously Running Tasks）</news:title>
   <news:publication_date>2026-06-10T19:43:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699245</loc>
  <lastmod>2026-06-10T19:43:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行列変量の歪んだ混合ビリニア因子解析（Mixtures of Skewed Matrix Variate Bilinear Factor Analyzers）</news:title>
   <news:publication_date>2026-06-10T19:43:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699243</loc>
  <lastmod>2026-06-10T19:42:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群ベースの分離表現学習と新規コンテンツへの一般化（Group-based Learning of Disentangled Representations with Generalizability for Novel Contents）</news:title>
   <news:publication_date>2026-06-10T19:42:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699241</loc>
  <lastmod>2026-06-10T19:42:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>On2Vecによるオントロジー充填の新展開（On2Vec: Embedding-based Relation Prediction for Ontology Population）</news:title>
   <news:publication_date>2026-06-10T19:42:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699239</loc>
  <lastmod>2026-06-10T18:51:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WCE画像における胃潰瘍検出のための無限カリキュラム学習（Infinite Curriculum Learning for Efficiently Detecting Gastric Ulcers in WCE Images）</news:title>
   <news:publication_date>2026-06-10T18:51:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699237</loc>
  <lastmod>2026-06-10T18:51:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AIがブラック・ショールズ方程式数値解法の次元の呪いを克服する証明（A proof that artificial neural networks overcome the curse of dimensionality in the numerical approximation of Black-Scholes partial differential equations）</news:title>
   <news:publication_date>2026-06-10T18:51:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699235</loc>
  <lastmod>2026-06-10T18:51:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタパス埋め込みによる知識グラフの特徴学習（Feature Learning for Meta-Paths in Knowledge Graphs）</news:title>
   <news:publication_date>2026-06-10T18:51:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699233</loc>
  <lastmod>2026-06-10T18:50:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報理論に基づく能動学習で効率的に画像検索を改善する（Information-Theoretic Active Learning for Content-Based Image Retrieval）</news:title>
   <news:publication_date>2026-06-10T18:50:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699231</loc>
  <lastmod>2026-06-10T18:50:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形最適化向けの高速アンダーソン・チェビシェフ加速（A Fast Anderson-Chebyshev Acceleration for Nonlinear Optimization）</news:title>
   <news:publication_date>2026-06-10T18:50:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699229</loc>
  <lastmod>2026-06-10T18:49:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチターゲット予測の統一的視点（Multi-target prediction: A unifying view on problems and methods）</news:title>
   <news:publication_date>2026-06-10T18:49:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699227</loc>
  <lastmod>2026-06-10T18:49:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNと手作り特徴の融合で肺結節の悪性度を予測する手法（Predicting Lung Nodule Malignancies by Combining Deep Convolutional Neural Network and Handcrafted Features）</news:title>
   <news:publication_date>2026-06-10T18:49:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699225</loc>
  <lastmod>2026-06-10T17:58:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模閉ループ産業プロセスの分散動的モデリングとモニタリング（Distributed dynamic modeling and monitoring for large-scale industrial processes under closed-loop control）</news:title>
   <news:publication_date>2026-06-10T17:58:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699223</loc>
  <lastmod>2026-06-10T17:57:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速グリーディ法による辞書選択と一般化スパース制約（Fast greedy algorithms for dictionary selection with generalized sparsity constraints）</news:title>
   <news:publication_date>2026-06-10T17:57:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699221</loc>
  <lastmod>2026-06-10T17:57:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>掘進機の運転データから地質を予測する手法の実用性（Geology prediction based on operation data of TBM: comparison between deep neural network and statistical learning methods）</news:title>
   <news:publication_date>2026-06-10T17:57:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699219</loc>
  <lastmod>2026-06-10T17:56:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平均分散最適化のためのブロック座標上昇アルゴリズム（A Block Coordinate Ascent Algorithm for Mean-Variance Optimization）</news:title>
   <news:publication_date>2026-06-10T17:56:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699217</loc>
  <lastmod>2026-06-10T17:56:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多言語ニューラル言語モデルによる教師なしクロスリンガル単語埋め込み（Unsupervised Cross-lingual Word Embedding by Multilingual Neural Language Models）</news:title>
   <news:publication_date>2026-06-10T17:56:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699215</loc>
  <lastmod>2026-06-10T17:56:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在空間でのランク最小化によるテンソルリング補完（Tensor Ring Decomposition with Rank Minimization on Latent Space）</news:title>
   <news:publication_date>2026-06-10T17:56:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699213</loc>
  <lastmod>2026-06-10T17:55:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューロン統合層による漸進的冗長性削減（Neurons Merging Layer: Towards Progressive Redundancy Reduction for Deep Supervised Hashing）</news:title>
   <news:publication_date>2026-06-10T17:55:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699211</loc>
  <lastmod>2026-06-10T17:04:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関係的プログラム合成（Relational Program Synthesis）</news:title>
   <news:publication_date>2026-06-10T17:04:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699209</loc>
  <lastmod>2026-06-10T17:04:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的クラスタリングの近似アルゴリズム（Approximation algorithms for stochastic clustering）</news:title>
   <news:publication_date>2026-06-10T17:04:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699207</loc>
  <lastmod>2026-06-10T17:03:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト付き有向ネットワークの埋め込み学習（Learning Embeddings of Directed Networks with Text-Associated Nodes—with Application in Software Package Dependency Networks）</news:title>
   <news:publication_date>2026-06-10T17:03:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699205</loc>
  <lastmod>2026-06-10T17:02:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BubGANによる気泡流画像合成（BubGAN: Bubble Generative Adversarial Networks for Synthesizing Realistic Bubbly Flow Images）</news:title>
   <news:publication_date>2026-06-10T17:02:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699203</loc>
  <lastmod>2026-06-10T17:02:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロジスティック回帰で背景ノードを除外するネットワークのコミュニティ検出（Logistic Regression Augmented Community Detection for Network Data）</news:title>
   <news:publication_date>2026-06-10T17:02:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699201</loc>
  <lastmod>2026-06-10T17:02:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動優性多発性嚢胞腎のCT画像から腎臓総量を算出する多目的3D畳み込みニューラルネットワーク（Computation of Total Kidney Volume from CT images in Autosomal Dominant Polycystic Kidney Disease using Multi-Task 3D Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-10T17:02:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699199</loc>
  <lastmod>2026-06-10T17:02:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジ意味を考慮した表現学習が変えるバイオ医療知識発見（edge2vec: Representation learning using edge semantics for biomedical knowledge discovery）</news:title>
   <news:publication_date>2026-06-10T17:02:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699197</loc>
  <lastmod>2026-06-10T16:10:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチソースからのドメイン適応を重み付き専門家で行う考え方（Multi-Source Domain Adaptation with Mixture of Experts）</news:title>
   <news:publication_date>2026-06-10T16:10:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699195</loc>
  <lastmod>2026-06-10T16:10:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超小型矮小銀河候補の本質（On the Nature of Ultra-faint Dwarf Galaxy Candidates. III. Horologium I, Pictor I, Grus I, and Phoenix II）</news:title>
   <news:publication_date>2026-06-10T16:10:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699193</loc>
  <lastmod>2026-06-10T16:09:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォーラム間で学ぶ重複質問検出の実用性（Adversarial Domain Adaptation for Duplicate Question Detection）</news:title>
   <news:publication_date>2026-06-10T16:09:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699191</loc>
  <lastmod>2026-06-10T16:08:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共有入力を持つ合成関数に対する量子アルゴリズムと近似多項式（Quantum algorithms and approximating polynomials for composed functions with shared inputs）</news:title>
   <news:publication_date>2026-06-10T16:08:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699189</loc>
  <lastmod>2026-06-10T16:08:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイクル一貫性を用いた音声強調（Cycle-Consistent Speech Enhancement）</news:title>
   <news:publication_date>2026-06-10T16:08:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699187</loc>
  <lastmod>2026-06-10T16:08:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的特徴変換による音声強調（Adversarial Feature-Mapping for Speech Enhancement）</news:title>
   <news:publication_date>2026-06-10T16:08:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699185</loc>
  <lastmod>2026-06-10T16:08:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適な公平政策の学習（Learning Optimal Fair Policies）</news:title>
   <news:publication_date>2026-06-10T16:08:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699183</loc>
  <lastmod>2026-06-10T15:16:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重要インフラに対する適応型戦略的サイバー防御（Adaptive Strategic Cyber Defense for Advanced Persistent Threats in Critical Infrastructure Networks）</news:title>
   <news:publication_date>2026-06-10T15:16:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699181</loc>
  <lastmod>2026-06-10T15:09:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多腕バンディット的アプローチによる多重検定と偽発見率制御（A Bandit Approach to Multiple Testing with False Discovery Control）</news:title>
   <news:publication_date>2026-06-10T15:09:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699179</loc>
  <lastmod>2026-06-10T15:09:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2段階フィルタ剪定によるCNN圧縮（Two-Phase Filter Pruning Based on Conditional Entropy）</news:title>
   <news:publication_date>2026-06-10T15:09:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699177</loc>
  <lastmod>2026-06-10T15:08:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プレイヤー経験をゲーム映像から抽出する方法（Player Experience Extraction from Gameplay Video）</news:title>
   <news:publication_date>2026-06-10T15:08:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699175</loc>
  <lastmod>2026-06-10T15:08:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープラーニングによるデリバティブ評価の革新（Deeply Learning Derivatives）</news:title>
   <news:publication_date>2026-06-10T15:08:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699173</loc>
  <lastmod>2026-06-10T15:07:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチチャネル・マルチタッチ帰属に対する注意機構付き深層ニューラルネット（Deep Neural Net with Attention for Multi-channel Multi-touch Attribution）</news:title>
   <news:publication_date>2026-06-10T15:07:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699171</loc>
  <lastmod>2026-06-10T15:06:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パターン化画像におけるユーザーマーキングの内容に基づく伝播（Content-based Propagation of User Markings for Interactive Segmentation of Patterned Images）</news:title>
   <news:publication_date>2026-06-10T15:06:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699169</loc>
  <lastmod>2026-06-10T14:15:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈と時間の課題に挑む強化学習ベンチマーク：Space Fortressの導入（Challenges of Context and Time in Reinforcement Learning: Introducing Space Fortress as a Benchmark）</news:title>
   <news:publication_date>2026-06-10T14:15:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699167</loc>
  <lastmod>2026-06-10T14:14:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dynamic Hierarchical Empirical Bayes を用いたオンライン広告予測の実務的意義（Dynamic Hierarchical Empirical Bayes: A Predictive Model Applied to Online Advertising）</news:title>
   <news:publication_date>2026-06-10T14:14:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699165</loc>
  <lastmod>2026-06-10T14:14:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ProdSumNetによるパラメータ削減の実務的示唆（ProdSumNet: reducing model parameters in deep neural networks via product-of-sums matrix decompositions）</news:title>
   <news:publication_date>2026-06-10T14:14:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699163</loc>
  <lastmod>2026-06-10T14:14:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>論理ルール誘導と理論学習をニューラル定理証明で実現する手法（Logical Rule Induction and Theory Learning Using Neural Theorem Proving）</news:title>
   <news:publication_date>2026-06-10T14:14:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699161</loc>
  <lastmod>2026-06-10T14:13:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ的非パラメトリックスペクトル推定（Bayesian Nonparametric Spectral Estimation）</news:title>
   <news:publication_date>2026-06-10T14:13:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699159</loc>
  <lastmod>2026-06-10T14:13:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バイアスとスプリアス変動を明示的に除去する方法（Turning a Blind Eye: Explicit Removal of Biases and Variation from Deep Neural Network Embeddings）</news:title>
   <news:publication_date>2026-06-10T14:13:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699157</loc>
  <lastmod>2026-06-10T14:13:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>指数族モデルに対する差分プライバシー下のベイズ推論（Differentially Private Bayesian Inference for Exponential Families）</news:title>
   <news:publication_date>2026-06-10T14:13:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699155</loc>
  <lastmod>2026-06-10T13:22:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付き最適化におけるサドルポイント回避の方法（Escaping Saddle Points in Constrained Optimization）</news:title>
   <news:publication_date>2026-06-10T13:22:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699153</loc>
  <lastmod>2026-06-10T13:21:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般物体検出における深層学習の総覧（Deep Learning for Generic Object Detection: A Survey）</news:title>
   <news:publication_date>2026-06-10T13:21:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699151</loc>
  <lastmod>2026-06-10T13:21:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>基地局のオン／オフ制御を深層強化学習で最適化する手法（DRAG: Deep Reinforcement Learning Based Base Station Activation in Heterogeneous Networks）</news:title>
   <news:publication_date>2026-06-10T13:21:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699149</loc>
  <lastmod>2026-06-10T13:20:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像キャプションにおける物体誤認（Object Hallucination in Image Captioning）</news:title>
   <news:publication_date>2026-06-10T13:20:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699147</loc>
  <lastmod>2026-06-10T13:20:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頑健なストリーミングテンソル分解と補完の変分ベイズ推論（Variational Bayesian Inference for Robust Streaming Tensor Factorization and Completion）</news:title>
   <news:publication_date>2026-06-10T13:20:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699145</loc>
  <lastmod>2026-06-10T13:20:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FATSからfeetsへ：天文時系列特徴抽出ツール改良の要点（From FATS to feets: Further improvements to an astronomical feature extraction tool based on machine learning）</news:title>
   <news:publication_date>2026-06-10T13:20:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699143</loc>
  <lastmod>2026-06-10T13:19:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再現核クレイン空間におけるスケーラブル学習（Scalable Learning in Reproducing Kernel Krein Spaces）</news:title>
   <news:publication_date>2026-06-10T13:19:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699133</loc>
  <lastmod>2026-06-10T12:28:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>類似度ベースのスペクトル解析による地理的表現の強化（Deriving Enhanced Geographical Representations via Similarity-based Spectral Analysis: Predicting Colorectal Cancer Survival Curves in Iowa）</news:title>
   <news:publication_date>2026-06-10T12:28:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699131</loc>
  <lastmod>2026-06-10T12:28:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローマ字化サンスクリットのOCR再利用によるポストOCR誤り訂正（Upcycle Your OCR: Reusing OCRs for Post-OCR Text Correction in Romanised Sanskrit）</news:title>
   <news:publication_date>2026-06-10T12:28:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699129</loc>
  <lastmod>2026-06-10T12:28:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発散最小化を超えるGAN（GANs beyond divergence minimization）</news:title>
   <news:publication_date>2026-06-10T12:28:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699127</loc>
  <lastmod>2026-06-10T12:27:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANによる有効場理論モデル生成（GANs for generating EFT models）</news:title>
   <news:publication_date>2026-06-10T12:27:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699125</loc>
  <lastmod>2026-06-10T12:27:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造的一貫性と制御性を両立する多様な彩色（Structural Consistency and Controllability for Diverse Colorization）</news:title>
   <news:publication_date>2026-06-10T12:27:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699123</loc>
  <lastmod>2026-06-10T12:27:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河中心マグネターの電波パルス形状解析（Pulse Morphology of the Galactic Center Magnetar PSR J1745–2900）</news:title>
   <news:publication_date>2026-06-10T12:27:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699121</loc>
  <lastmod>2026-06-10T12:26:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙シミュレーションで学ぶ遠方銀河合体の自動分類（Automated Distant Galaxy Merger Classifications from Space Telescope Images using the Illustris Simulation）</news:title>
   <news:publication_date>2026-06-10T12:26:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699119</loc>
  <lastmod>2026-06-10T11:35:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学ぶべきでない行動の見切り術（Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-10T11:35:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699117</loc>
  <lastmod>2026-06-10T11:35:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>報酬スケーリングと適応ネットワークスケーリング（Adaptive Network Scaling for Deep Rectifier Reinforcement Learning Models）</news:title>
   <news:publication_date>2026-06-10T11:35:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699115</loc>
  <lastmod>2026-06-10T11:35:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚と音声で読む話し言葉の大規模自動認識（Deep Audio-Visual Speech Recognition）</news:title>
   <news:publication_date>2026-06-10T11:35:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699113</loc>
  <lastmod>2026-06-10T11:34:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メモリーネットワークによる多変量時系列予測の解法（A Memory-Network Based Solution for Multivariate Time-Series Forecasting）</news:title>
   <news:publication_date>2026-06-10T11:34:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699111</loc>
  <lastmod>2026-06-10T11:34:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語埋め込みにおける発散する言語情報の発見（Uncovering divergent linguistic information in word embeddings with lessons for intrinsic and extrinsic evaluation）</news:title>
   <news:publication_date>2026-06-10T11:34:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699109</loc>
  <lastmod>2026-06-10T11:33:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IDSGANによる侵入検知回避攻撃の生成（IDSGAN: Generative Adversarial Networks for Attack Generation against Intrusion Detection）</news:title>
   <news:publication_date>2026-06-10T11:33:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699107</loc>
  <lastmod>2026-06-10T11:33:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的例は不可避か？（Are Adversarial Examples Inevitable?）</news:title>
   <news:publication_date>2026-06-10T11:33:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699105</loc>
  <lastmod>2026-06-10T10:41:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市交通シーンにおけるマルチクラス物体検出器を用いた複数物体追跡（Multiple Object Tracking in Urban Traffic Scenes with a Multiclass Object Detector）</news:title>
   <news:publication_date>2026-06-10T10:41:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699103</loc>
  <lastmod>2026-06-10T10:31:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>in vitro用製剤予測のためのディープラーニング（Deep learning for in vitro prediction of pharmaceutical formulations）</news:title>
   <news:publication_date>2026-06-10T10:31:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699101</loc>
  <lastmod>2026-06-10T10:31:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ARCHERによるHERのバイアス是正（ARCHER: Aggressive Rewards to Counter bias in Hindsight Experience Replay）</news:title>
   <news:publication_date>2026-06-10T10:31:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699099</loc>
  <lastmod>2026-06-10T10:30:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次元確率的構成ネットワークを画像解析に活かす（Two Dimensional Stochastic Configuration Networks for Image Data Analytics）</news:title>
   <news:publication_date>2026-06-10T10:30:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699097</loc>
  <lastmod>2026-06-10T10:30:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>新しいカテゴリを忘れずに生成する仕組み（Memory Replay GANs: learning to generate images from new categories without forgetting）</news:title>
   <news:publication_date>2026-06-10T10:30:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699095</loc>
  <lastmod>2026-06-10T10:30:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>（121514）1999 UJ7：原始的で遅い回転を示す火星トロヤ群小惑星（(121514) 1999 UJ7: A primitive, slow-rotating Martian Trojan）</news:title>
   <news:publication_date>2026-06-10T10:30:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699093</loc>
  <lastmod>2026-06-10T10:30:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプル効率の高い模倣学習（Sample-Efficient Imitation Learning via Generative Adversarial Nets）</news:title>
   <news:publication_date>2026-06-10T10:30:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699091</loc>
  <lastmod>2026-06-10T09:38:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Seq2seq出力の統語的性質評価と広範囲HPSGの活用（Evaluating Syntactic Properties of Seq2seq Output with a Broad Coverage HPSG: A Case Study on Machine Translation）</news:title>
   <news:publication_date>2026-06-10T09:38:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699089</loc>
  <lastmod>2026-06-10T09:38:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビン化データに対するガウス過程回帰（Gaussian Process Regression for Binned Data）</news:title>
   <news:publication_date>2026-06-10T09:38:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699087</loc>
  <lastmod>2026-06-10T09:38:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽フレア由来ニュートリノとメガトン検出器が変える宇宙飛行の安全性（Solar neutrino flare, megaton neutrino detectors and human space journey）</news:title>
   <news:publication_date>2026-06-10T09:38:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699085</loc>
  <lastmod>2026-06-10T09:37:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>密なポーズ転送（Dense Pose Transfer）</news:title>
   <news:publication_date>2026-06-10T09:37:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699083</loc>
  <lastmod>2026-06-10T09:37:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>産業用センサデータの超解像知覚（Super Resolution Perception of Industrial Sensor Data）</news:title>
   <news:publication_date>2026-06-10T09:37:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699081</loc>
  <lastmod>2026-06-10T09:36:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二方向問答ネットワークによる機械読解（Dual Ask-Answer Network for Machine Reading Comprehension）</news:title>
   <news:publication_date>2026-06-10T09:36:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699079</loc>
  <lastmod>2026-06-10T09:36:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点描法に学ぶ単一画像からの3D復元（3D Surface Reconstruction by Pointillism）</news:title>
   <news:publication_date>2026-06-10T09:36:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699077</loc>
  <lastmod>2026-06-10T08:45:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様性とスパース性：インデックス・トラッキングの新視点（DIVERSITY AND SPARSITY: A NEW PERSPECTIVE ON INDEX TRACKING）</news:title>
   <news:publication_date>2026-06-10T08:45:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699075</loc>
  <lastmod>2026-06-10T08:45:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量的推定の評価指標の検討（Evaluation Measures for Quantification）</news:title>
   <news:publication_date>2026-06-10T08:45:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699073</loc>
  <lastmod>2026-06-10T08:45:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>年齢層を考慮したマルチエキスパートによる性別分類（Multi-Expert Gender Classification on Age Group by Integrating Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-10T08:45:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699071</loc>
  <lastmod>2026-06-10T08:43:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バランス化されたマルチショットEPIを用いた高速Cartesian MRF（Balanced multi-shot EPI for accelerated Cartesian MRF: An alternative to spiral MRF）</news:title>
   <news:publication_date>2026-06-10T08:43:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699069</loc>
  <lastmod>2026-06-10T08:43:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コードスイッチ言語モデルの改良（Code-switched Language Models Using Dual RNNs and Same-Source Pretraining）</news:title>
   <news:publication_date>2026-06-10T08:43:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699067</loc>
  <lastmod>2026-06-10T08:43:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度指紋画像における孔（ポア）検出とDeepResPore（Pore detection in high-resolution fingerprint images using Deep Residual Network）</news:title>
   <news:publication_date>2026-06-10T08:43:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699065</loc>
  <lastmod>2026-06-10T08:43:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Particle Swarm Optimizationクラスタリング入門（A tutorial on Particle Swarm Optimization Clustering）</news:title>
   <news:publication_date>2026-06-10T08:43:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699063</loc>
  <lastmod>2026-06-10T07:51:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的制御を用いた合成最適化の新手法（Stochastically Controlled Stochastic Gradient for the Convex and Non-convex Composition problem）</news:title>
   <news:publication_date>2026-06-10T07:51:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699061</loc>
  <lastmod>2026-06-10T07:51:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線で捉える空気シャワーのリアルタイム検出（Towards online triggering for the radio detection of air showers using deep neural networks）</news:title>
   <news:publication_date>2026-06-10T07:51:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699059</loc>
  <lastmod>2026-06-10T07:49:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズA最適設計とグループラッソーの意外な接点（An unexpected connection between Bayes A-optimal designs and the Group Lasso）</news:title>
   <news:publication_date>2026-06-10T07:49:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699057</loc>
  <lastmod>2026-06-10T07:49:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>固定集合探索（Fixed Set Search）を巡る考察（Fixed set search applied to the traveling salesman problem）</news:title>
   <news:publication_date>2026-06-10T07:49:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699055</loc>
  <lastmod>2026-06-10T07:49:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gaussian Processesをゼロから実装する実践ハンドブック（Hands-on Experience with Gaussian Processes (GPs): Implementing GPs in Python - I）</news:title>
   <news:publication_date>2026-06-10T07:49:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699053</loc>
  <lastmod>2026-06-10T07:48:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一撃学習でのiEEG発作検出—二値化処理と高次元コンピューティングの融合（One-shot Learning for iEEG Seizure Detection Using End-to-end Binary Operations）</news:title>
   <news:publication_date>2026-06-10T07:48:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699051</loc>
  <lastmod>2026-06-10T07:48:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リッチデータが貧弱データを助ける模倣学習（RDPD: Rich Data Helps Poor Data via Imitation）</news:title>
   <news:publication_date>2026-06-10T07:48:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699049</loc>
  <lastmod>2026-06-10T06:56:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全身高解像度アニメ生成のための段階的構造条件付GAN（Full-body High-resolution Anime Generation with Progressive Structure-conditional Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-10T06:56:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699047</loc>
  <lastmod>2026-06-10T06:56:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒエラルキー化CNNとLSTMによる走行速度予測（Travel Speed Prediction with a Hierarchical Convolutional Neural Network and Long Short-Term Memory Model Framework）</news:title>
   <news:publication_date>2026-06-10T06:56:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699045</loc>
  <lastmod>2026-06-10T06:56:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルベース正則化を使った深層強化学習（Model-Based Regularization for Deep Reinforcement Learning with Transcoder Networks）</news:title>
   <news:publication_date>2026-06-10T06:56:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699043</loc>
  <lastmod>2026-06-10T06:55:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マーケットプレイス向け深層ニューラルレコメンダーの5つの教訓（Five lessons from building a deep neural network recommender for marketplaces）</news:title>
   <news:publication_date>2026-06-10T06:55:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699041</loc>
  <lastmod>2026-06-10T06:55:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的文脈の重要性とシーン理解におけるデータ拡張の役割（On the Importance of Visual Context for Data Augmentation in Scene Understanding）</news:title>
   <news:publication_date>2026-06-10T06:55:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699039</loc>
  <lastmod>2026-06-10T06:55:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CoverBLIP：スケーラブル反復マッチドフィルタリングによるMR Fingerprint回復（CoverBLIP: scalable iterative matched filtering for MR Fingerprint recovery）</news:title>
   <news:publication_date>2026-06-10T06:55:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699037</loc>
  <lastmod>2026-06-10T06:54:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定で解釈可能な予測とKnockoffs推論（IPAD: Stable Interpretable Forecasting with Knockoffs Inference）</news:title>
   <news:publication_date>2026-06-10T06:54:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699035</loc>
  <lastmod>2026-06-10T06:03:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約列符号の深層学習による復号化（Deep Learning-Based Decoding for Constrained Sequence Codes）</news:title>
   <news:publication_date>2026-06-10T06:03:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699033</loc>
  <lastmod>2026-06-10T06:02:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マーケットプレイスにおける深層ニューラルネットワーク推薦器のオンライン実験（Deep neural network marketplace recommenders in online experiments）</news:title>
   <news:publication_date>2026-06-10T06:02:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699031</loc>
  <lastmod>2026-06-10T06:02:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GAMENet：薬物併用の安全性を考慮したメモリ拡張グラフネットワーク（GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination）</news:title>
   <news:publication_date>2026-06-10T06:02:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699029</loc>
  <lastmod>2026-06-10T06:01:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木探索を組み合わせる強化学習の実践的示唆（How to Combine Tree-Search Methods in Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-10T06:01:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699027</loc>
  <lastmod>2026-06-10T06:01:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視点不変な動作表現の教師なし学習（Unsupervised Learning of View-invariant Action Representations）</news:title>
   <news:publication_date>2026-06-10T06:01:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699025</loc>
  <lastmod>2026-06-10T06:01:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoU損失は部分加法性である（Yes, IoU loss is submodular – as a function of the mispredictions）</news:title>
   <news:publication_date>2026-06-10T06:01:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699023</loc>
  <lastmod>2026-06-10T06:00:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習ベースの物体検出器作成支援（Guiding the Creation of Deep Learning-based Object Detectors）</news:title>
   <news:publication_date>2026-06-10T06:00:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699021</loc>
  <lastmod>2026-06-10T05:09:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーグラフ上のWassersteinソフトラベル伝播（Wasserstein Soft Label Propagation on Hypergraphs: Algorithm and Generalization Error Bounds）</news:title>
   <news:publication_date>2026-06-10T05:09:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699019</loc>
  <lastmod>2026-06-10T05:08:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト分類ニューラルネットワークの敵対的再プログラミング（Adversarial Reprogramming of Text Classification Neural Networks）</news:title>
   <news:publication_date>2026-06-10T05:08:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699017</loc>
  <lastmod>2026-06-10T05:08:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>固有分解を不要にしたグラフ信号のサンプリング選択（Eigendecomposition-Free Sampling Set Selection for Graph Signals）</news:title>
   <news:publication_date>2026-06-10T05:08:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699015</loc>
  <lastmod>2026-06-10T05:07:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アニーリング変分目的による変分推論の探索性向上（Improving Explorability in Variational Inference with Annealed Variational Objectives）</news:title>
   <news:publication_date>2026-06-10T05:07:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699013</loc>
  <lastmod>2026-06-10T05:07:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運転経験の転移によるエンドツーエンド自動運転制御（Driving Experience Transfer Method for End-to-End Control of Self-Driving Cars）</news:title>
   <news:publication_date>2026-06-10T05:07:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699011</loc>
  <lastmod>2026-06-10T05:07:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズの多い時系列データにおけるモチーフ認識と状態割当（MASA: Motif-Aware State Assignment in Noisy Time Series Data）</news:title>
   <news:publication_date>2026-06-10T05:07:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699009</loc>
  <lastmod>2026-06-10T05:06:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像のノイズ除去と高次視覚タスクの連携（Connecting Image Denoising and High-Level Vision Tasks via Deep Learning）</news:title>
   <news:publication_date>2026-06-10T05:06:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699007</loc>
  <lastmod>2026-06-10T04:15:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン適応型画像再構成（Online Adaptive Image Reconstruction (OnAIR) Using Dictionary Models）</news:title>
   <news:publication_date>2026-06-10T04:15:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699005</loc>
  <lastmod>2026-06-10T04:14:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模動画オブジェクトセグメンテーションデータセットの構築が変えたこと（YouTube-VOS: A Large-Scale Video Object Segmentation Benchmark）</news:title>
   <news:publication_date>2026-06-10T04:14:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699003</loc>
  <lastmod>2026-06-10T04:14:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大型二十面体ウイルスが足場タンパク質を必要とする理由（Why large icosahedral viruses need scaffolding proteins: The interplay of Gaussian curvature and disclination interactions）</news:title>
   <news:publication_date>2026-06-10T04:14:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699001</loc>
  <lastmod>2026-06-10T04:13:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化知識ベースの自然言語生成（Describing a Knowledge Base）</news:title>
   <news:publication_date>2026-06-10T04:13:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698999</loc>
  <lastmod>2026-06-10T04:13:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付きモデルにおけるNoise Contrastive EstimationとNegative Samplingの整合性と効率（Noise Contrastive Estimation and Negative Sampling for Conditional Models: Consistency and Statistical Efficiency）</news:title>
   <news:publication_date>2026-06-10T04:13:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698997</loc>
  <lastmod>2026-06-10T04:13:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元高階データの最適スパース特異値分解（Optimal Sparse Singular Value Decomposition for High-dimensional High-order Data）</news:title>
   <news:publication_date>2026-06-10T04:13:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698995</loc>
  <lastmod>2026-06-10T04:12:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変数自己符号化器における影響因子の発見（Discovering Influential Factors in Variational Autoencoder）</news:title>
   <news:publication_date>2026-06-10T04:12:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698993</loc>
  <lastmod>2026-06-10T03:22:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MDCNによる物体検出の効率化（Multi-Scale, Deep Inception Convolutional Neural Networks for Efficient Object Detection）</news:title>
   <news:publication_date>2026-06-10T03:22:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698991</loc>
  <lastmod>2026-06-10T03:21:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AMIネットワークにおける深層再帰型不正電力検知（Deep Recurrent Electricity Theft Detection in AMI Networks with Random Tuning of Hyper-parameters）</news:title>
   <news:publication_date>2026-06-10T03:21:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698989</loc>
  <lastmod>2026-06-10T03:21:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチビュー因子化オートエンコーダとネットワーク制約によるマルチオミク統合解析（Multi-view Factorization AutoEncoder with Network Constraints for Multi-omic Integrative Analysis）</news:title>
   <news:publication_date>2026-06-10T03:21:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698987</loc>
  <lastmod>2026-06-10T03:20:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>収束基準と機械学習によるMonkhorst-Pack k点および平面波カットオフ予測（Convergence and machine learning predictions of Monkhorst-Pack k-points and plane-wave cut-off in high-throughput DFT calculations）</news:title>
   <news:publication_date>2026-06-10T03:20:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698985</loc>
  <lastmod>2026-06-10T03:20:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層化テキスト分類と単語埋め込みの実践的解析（An Analysis of Hierarchical Text Classification Using Word Embeddings）</news:title>
   <news:publication_date>2026-06-10T03:20:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698983</loc>
  <lastmod>2026-06-10T03:20:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測下での効率的な確率的スパース回帰手法（Sample Efficient Stochastic Gradient Iterative Hard Thresholding Method for Stochastic Sparse Linear Regression with Limited Attribute Observation）</news:title>
   <news:publication_date>2026-06-10T03:20:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698981</loc>
  <lastmod>2026-06-10T03:19:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチフィンガー二分探索木の概説（Multi-finger binary search trees）</news:title>
   <news:publication_date>2026-06-10T03:19:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698979</loc>
  <lastmod>2026-06-10T02:28:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カルネギー・シカゴ・ハッブル・プログラム V：赤色巨星分岐点によるNGC 1448とNGC 1316の距離測定 (THE CARNEGIE-CHICAGO HUBBLE PROGRAM. V. THE DISTANCES TO NGC 1448 AND NGC 1316 VIA THE TIP OF THE RED GIANT BRANCH)</news:title>
   <news:publication_date>2026-06-10T02:28:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698977</loc>
  <lastmod>2026-06-10T02:28:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>喫煙イベント予測のための時変半パラメトリックホーキス過程（Predicting Smoking Events with a Time-Varying Semi-Parametric Hawkes Process Model）</news:title>
   <news:publication_date>2026-06-10T02:28:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698975</loc>
  <lastmod>2026-06-10T02:27:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習でMRFの辞書負荷を60倍削減する方法（GEOMETRY OF DEEP LEARNING FOR MAGNETIC RESONANCE FINGERPRINTING）</news:title>
   <news:publication_date>2026-06-10T02:27:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698973</loc>
  <lastmod>2026-06-10T02:27:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習と暗号理論を結ぶ敵対的攻撃防御の考え方（Bridging machine learning and cryptography in defence against adversarial attacks）</news:title>
   <news:publication_date>2026-06-10T02:27:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698971</loc>
  <lastmod>2026-06-10T02:26:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声と映像を揃えて雑音に強くする方法（Attention-based Audio-Visual Fusion for Robust Automatic Speech Recognition）</news:title>
   <news:publication_date>2026-06-10T02:26:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698969</loc>
  <lastmod>2026-06-10T02:26:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイド情報による単一コミュニティ復元の情報理論的限界（Recovering a Single Community with Side Information）</news:title>
   <news:publication_date>2026-06-10T02:26:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698967</loc>
  <lastmod>2026-06-10T02:26:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>放射線画像と3D畳み込みを融合した頸部リンパ節転移予測（Combining Many-objective Radiomics and 3-dimensional Convolutional Neural Network through Evidential Reasoning to Predict Lymph Node Metastasis in Head and Neck Cancer）</news:title>
   <news:publication_date>2026-06-10T02:26:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698965</loc>
  <lastmod>2026-06-10T01:34:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カバレッジベースのサンプル設計によるハイパーパラメータ最適化の改善（Improving Hyper-Parameter Optimization Using Coverage-Based Sample Designs）</news:title>
   <news:publication_date>2026-06-10T01:34:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698963</loc>
  <lastmod>2026-06-10T01:34:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幹細胞の時空間動態を数理で解く（Statistical and mathematical modeling of spatiotemporal dynamics of stem cells）</news:title>
   <news:publication_date>2026-06-10T01:34:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698961</loc>
  <lastmod>2026-06-10T01:33:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーボリック空間でのメトリック学習によるレコメンダー性能向上（HyperML: A Boosting Metric Learning Approach in Hyperbolic Space for Recommender Systems）</news:title>
   <news:publication_date>2026-06-10T01:33:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698959</loc>
  <lastmod>2026-06-10T01:32:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語彙予測による文生成の強化学習高速化（Accelerated Reinforcement Learning for Sentence Generation by Vocabulary Prediction）</news:title>
   <news:publication_date>2026-06-10T01:32:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698957</loc>
  <lastmod>2026-06-10T01:32:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マンモグラムにおける乳腺腫瘍のセグメンテーションと形状分類（Breast Tumor Segmentation and Shape Classification in Mammograms using Generative Adversarial and Convolutional Neural Network）</news:title>
   <news:publication_date>2026-06-10T01:32:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698955</loc>
  <lastmod>2026-06-10T01:32:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画における高速物体検出のための領域パッキング（Pack and Detect: Fast Object Detection in Videos Using Region-of-Interest Packing）</news:title>
   <news:publication_date>2026-06-10T01:32:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698953</loc>
  <lastmod>2026-06-10T01:31:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河検出と識別における深層学習とデータ拡張の実用化（Galaxy detection and identification using deep learning and data augmentation）</news:title>
   <news:publication_date>2026-06-10T01:31:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698951</loc>
  <lastmod>2026-06-10T00:40:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単視点深度とオプティカルフローの教師なし共同学習（DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistency）</news:title>
   <news:publication_date>2026-06-10T00:40:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698949</loc>
  <lastmod>2026-06-10T00:39:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元共通トレンド交絡を扱う効率的Difference-in-Differences推定（Efficient Difference-in-Differences Estimation with High-Dimensional Common Trend Confounding）</news:title>
   <news:publication_date>2026-06-10T00:39:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698947</loc>
  <lastmod>2026-06-10T00:39:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文書関連度ランキングの深層的改良（Deep Relevance Ranking Using Enhanced Document-Query Interactions）</news:title>
   <news:publication_date>2026-06-10T00:39:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698945</loc>
  <lastmod>2026-06-10T00:38:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子力学の理解を深める（Making Better Sense of Quantum Mechanics）</news:title>
   <news:publication_date>2026-06-10T00:38:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698943</loc>
  <lastmod>2026-06-10T00:38:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分プライバシー化されたWilcoxon符号付き順位検定の実装と意義（A Differentially Private Wilcoxon Signed-Rank Test）</news:title>
   <news:publication_date>2026-06-10T00:38:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698941</loc>
  <lastmod>2026-06-10T00:38:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>標的指向性を持つ分子設計の潜在空間最適化（Latent Molecular Optimization for Targeted Therapeutic Design）</news:title>
   <news:publication_date>2026-06-10T00:38:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698939</loc>
  <lastmod>2026-06-10T00:37:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な自分視点の視覚認識（Efficient Egocentric Visual Perception）</news:title>
   <news:publication_date>2026-06-10T00:37:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698937</loc>
  <lastmod>2026-06-09T23:46:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的分類器選択のためのオンライン局所プール生成（Online local pool generation for dynamic classifier selection: an extended version）</news:title>
   <news:publication_date>2026-06-09T23:46:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698935</loc>
  <lastmod>2026-06-09T23:45:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文字・単語埋め込みを用いたテキスト正規化（Utilizing Character and Word Embeddings for Text Normalization with Sequence-to-Sequence Models）</news:title>
   <news:publication_date>2026-06-09T23:45:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698933</loc>
  <lastmod>2026-06-09T23:45:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネル法に基づく遺伝子シェービング（Gene Shaving using influence function of a kernel method）</news:title>
   <news:publication_date>2026-06-09T23:45:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698931</loc>
  <lastmod>2026-06-09T23:45:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストからの画像注釈自動生成のための2モーダルネットワークアーキテクチャ（Bimodal network architectures for automatic generation of image annotation from text）</news:title>
   <news:publication_date>2026-06-09T23:45:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698929</loc>
  <lastmod>2026-06-09T23:44:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データセット結合の深層学習による手法（Merging Datasets Through Deep learning）</news:title>
   <news:publication_date>2026-06-09T23:44:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698927</loc>
  <lastmod>2026-06-09T23:44:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠損値がある場合の異常検知の扱い（Anomaly Detection in the Presence of Missing Values）</news:title>
   <news:publication_date>2026-06-09T23:44:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698925</loc>
  <lastmod>2026-06-09T22:53:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GAN Labによる生成モデル学習の可視化と教育効果（GAN Lab: Understanding Complex Deep Generative Models using Interactive Visual Experimentation）</news:title>
   <news:publication_date>2026-06-09T22:53:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698923</loc>
  <lastmod>2026-06-09T22:52:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乳児との多者間マルチモーダル対話管理（Multimodal Dialogue Management for Multiparty Interaction with Infants）</news:title>
   <news:publication_date>2026-06-09T22:52:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698921</loc>
  <lastmod>2026-06-09T22:52:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>被写界深度ブラーを活用した深層深度推定（Deep Depth from Defocus: how can defocus blur improve 3D estimation using dense neural networks?）</news:title>
   <news:publication_date>2026-06-09T22:52:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698919</loc>
  <lastmod>2026-06-09T22:51:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脅威下の強化学習：Threatened Markov Decision Processes（Reinforcement Learning under Threats）</news:title>
   <news:publication_date>2026-06-09T22:51:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698917</loc>
  <lastmod>2026-06-09T22:51:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交通密度推定にCNNを用いる方法（Traffic Density Estimation using a Convolutional Neural Network）</news:title>
   <news:publication_date>2026-06-09T22:51:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698915</loc>
  <lastmod>2026-06-09T22:00:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学生の物理自己効力感の低下を社会的ネットワークの視点から読み解く（Beyond performance metrics: Examining a decrease in students’ physics self-efficacy through a social networks lens）</news:title>
   <news:publication_date>2026-06-09T22:00:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698913</loc>
  <lastmod>2026-06-09T21:49:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスペクトログラム融合による音響シーン分類の向上（Multi-Spectrogram Fusion for Acoustic Scene Classification）</news:title>
   <news:publication_date>2026-06-09T21:49:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698911</loc>
  <lastmod>2026-06-09T21:49:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的文脈感応型時間減衰アテンションによる対話モデルの改善（Dynamically Context-Sensitive Time-Decay Attention for Dialogue Modeling）</news:title>
   <news:publication_date>2026-06-09T21:49:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698909</loc>
  <lastmod>2026-06-09T21:49:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈付き多言語語形変化推定の実装と成果（Multilingual Inflection in Context with Explicit Morphosyntactic Decoding）</news:title>
   <news:publication_date>2026-06-09T21:49:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698907</loc>
  <lastmod>2026-06-09T21:48:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VLSTM：超長時系列を扱うLSTMの拡張（VLSTM: VERY LONG SHORT-TERM MEMORY NETWORKS FOR HIGH-FREQUENCY TRADING）</news:title>
   <news:publication_date>2026-06-09T21:48:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698905</loc>
  <lastmod>2026-06-09T21:48:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>液体の流れに関する人間の直感のモデル化（Modeling human intuitions about liquid flow with particle-based simulation）</news:title>
   <news:publication_date>2026-06-09T21:48:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698903</loc>
  <lastmod>2026-06-09T21:48:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ信号からコミュニティを「盲検出」する手法（Blind Community Detection from Low-rank Excitations of a Graph）</news:title>
   <news:publication_date>2026-06-09T21:48:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698901</loc>
  <lastmod>2026-06-09T20:57:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層バイレベル学習（Deep Bilevel Learning）</news:title>
   <news:publication_date>2026-06-09T20:57:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698899</loc>
  <lastmod>2026-06-09T20:56:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポートフォリオの分散投資とモデル不確実性（Portfolio diversification and model uncertainty: a robust dynamic mean-variance approach）</news:title>
   <news:publication_date>2026-06-09T20:56:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698897</loc>
  <lastmod>2026-06-09T20:56:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈から感情を推定するモデル（Sentylic at IEST 2018: Gated Recurrent Neural Network and Capsule Network Based Approach for Implicit Emotion Detection）</news:title>
   <news:publication_date>2026-06-09T20:56:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698895</loc>
  <lastmod>2026-06-09T20:55:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepVAEとGMMによる星団検出（Stellar Cluster Detection using GMM with Deep Variational Autoencoder）</news:title>
   <news:publication_date>2026-06-09T20:55:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698893</loc>
  <lastmod>2026-06-09T20:55:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コントラストが深層ニューラルネットワークにどう符号化されているか（How is Contrast Encoded in Deep Neural Networks?）</news:title>
   <news:publication_date>2026-06-09T20:55:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698891</loc>
  <lastmod>2026-06-09T20:55:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚病変解析のためのデータ拡張（Data Augmentation for Skin Lesion Analysis）</news:title>
   <news:publication_date>2026-06-09T20:55:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698889</loc>
  <lastmod>2026-06-09T20:55:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>修正されたクラス確率多様性に基づく共学習によるハイパースペクトル画像分類（Modified Diversity of Class Probability Estimation Co-training for Hyperspectral Image Classification）</news:title>
   <news:publication_date>2026-06-09T20:55:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698887</loc>
  <lastmod>2026-06-09T20:03:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間におけるスパイク層誤差再割り当て（SLAYER: Spike Layer Error Reassignment in Time）</news:title>
   <news:publication_date>2026-06-09T20:03:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698885</loc>
  <lastmod>2026-06-09T20:02:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共変性と反変性の再考（Covariance and Contravariance: A Fresh Look at an Old Issue）</news:title>
   <news:publication_date>2026-06-09T20:02:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698883</loc>
  <lastmod>2026-06-09T20:02:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚病変画像を高解像度で合成する手法（Generating Highly Realistic Images of Skin Lesions with GANs）</news:title>
   <news:publication_date>2026-06-09T20:02:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698881</loc>
  <lastmod>2026-06-09T20:01:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ほぼ等差数列として近づく素数の構造（Almost arithmetic progressions in the primes and other large sets）</news:title>
   <news:publication_date>2026-06-09T20:01:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698879</loc>
  <lastmod>2026-06-09T20:01:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知覚的識別器を用いた画像操作（Image Manipulation with Perceptual Discriminators）</news:title>
   <news:publication_date>2026-06-09T20:01:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698877</loc>
  <lastmod>2026-06-09T20:01:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大量のラベルなし顔データから識別力を引き出す合意駆動伝播（Consensus-Driven Propagation in Massive Unlabeled Data for Face Recognition）</news:title>
   <news:publication_date>2026-06-09T20:01:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698875</loc>
  <lastmod>2026-06-09T20:00:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>任意時点Hedgeアルゴリズムの確率的最適性（On the optimality of the Hedge algorithm in the stochastic regime）</news:title>
   <news:publication_date>2026-06-09T20:00:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698873</loc>
  <lastmod>2026-06-09T19:09:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク生成モデルの定量評価手法（Towards quantitative methods to assess network generative models）</news:title>
   <news:publication_date>2026-06-09T19:09:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698871</loc>
  <lastmod>2026-06-09T19:09:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SN 2013gyの初期光度曲線と前駆天体制約（The first 48: Discovery and progenitor constraints on the Type Ia supernova 2013gy）</news:title>
   <news:publication_date>2026-06-09T19:09:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698869</loc>
  <lastmod>2026-06-09T19:09:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチドメイン画像翻訳のための統一的特徴分離器（A Unified Feature Disentangler for Multi-Domain Image Translation and Manipulation）</news:title>
   <news:publication_date>2026-06-09T19:09:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698867</loc>
  <lastmod>2026-06-09T19:08:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゼロショット学習によるプログラミング教育の自動フィードバック（Zero Shot Learning for Code Education）</news:title>
   <news:publication_date>2026-06-09T19:08:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698865</loc>
  <lastmod>2026-06-09T19:08:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極端に少ない注釈で網膜血管を分割する手法（Retinal Vessel Segmentation under Extreme Low Annotation: A Generative Adversarial Network Approach）</news:title>
   <news:publication_date>2026-06-09T19:08:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698863</loc>
  <lastmod>2026-06-09T19:07:53Z</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・ヒューマンマッティング（Semantic Human Matting）</news:title>
   <news:publication_date>2026-06-09T19:07:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698861</loc>
  <lastmod>2026-06-09T19:07:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>独立カーネル近似法（Independent Kernel Approximator）</news:title>
   <news:publication_date>2026-06-09T19:07:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698859</loc>
  <lastmod>2026-06-09T18:15:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル知識ベース埋め込みによるKB補完（Embedding Multimodal Relational Data for Knowledge Base Completion）</news:title>
   <news:publication_date>2026-06-09T18:15:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698857</loc>
  <lastmod>2026-06-09T18:15:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話における新しい“声”を作るニューラルモデル（Neural MultiVoice Models for Expressing Novel Personalities in Dialog）</news:title>
   <news:publication_date>2026-06-09T18:15:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698855</loc>
  <lastmod>2026-06-09T18:15:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ChannelNetsによる軽量化の設計思想（ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions）</news:title>
   <news:publication_date>2026-06-09T18:15:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698853</loc>
  <lastmod>2026-06-09T18:14:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザ好みの学習とカレンダー文脈の理解によるイベントスケジューリング（Learning User Preferences and Understanding Calendar Contexts for Event Scheduling）</news:title>
   <news:publication_date>2026-06-09T18:14:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698851</loc>
  <lastmod>2026-06-09T18:14:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>優先的サンプリングによる存在/不在データと存在のみデータの融合（Preferential sampling for presence/absence data and for fusion of presence/absence data with presence-only data）</news:title>
   <news:publication_date>2026-06-09T18:14:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698849</loc>
  <lastmod>2026-06-09T18:14:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化最小二乗法におけるクロスバリデーション残差とCookの距離の関係（Cross validation residuals for generalised least squares and other correlated data models）</news:title>
   <news:publication_date>2026-06-09T18:14:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698847</loc>
  <lastmod>2026-06-09T18:14:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNNを心理言語学的被験者として扱う研究（RNNs as psycholinguistic subjects: Syntactic state and grammatical dependency）</news:title>
   <news:publication_date>2026-06-09T18:14:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698845</loc>
  <lastmod>2026-06-09T17:22:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的粒子最適化サンプリングと非漸近収束理論（Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory）</news:title>
   <news:publication_date>2026-06-09T17:22:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698843</loc>
  <lastmod>2026-06-09T17:21:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習に基づくロボット用オートフォーカス（A Robotic Auto-Focus System based on Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-09T17:21:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698841</loc>
  <lastmod>2026-06-09T17:21:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現（デノテーション）からのセマンティックパーシングにおける方策整形と一般化更新式（Policy Shaping and Generalized Update Equations for Semantic Parsing from Denotations）</news:title>
   <news:publication_date>2026-06-09T17:21:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698839</loc>
  <lastmod>2026-06-09T17:21:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模画像を用いた人間fMRIデータセットの公開（BOLD5000: A public fMRI dataset of 5000 images）</news:title>
   <news:publication_date>2026-06-09T17:21:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698837</loc>
  <lastmod>2026-06-09T17:21:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>鳥瞰視点による純粋視覚ベースの障害物検知（Developing a Purely Visual Based Obstacle Detection using Inverse Perspective Mapping）</news:title>
   <news:publication_date>2026-06-09T17:21:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698835</loc>
  <lastmod>2026-06-09T17:21:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>概念の抽象度を弱教師ありで推定する方法（Learning Concept Abstractness Using Weak Supervision）</news:title>
   <news:publication_date>2026-06-09T17:21:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698833</loc>
  <lastmod>2026-06-09T17:20:46Z</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モデルを作る挑戦——Unsupervised Statistical Machine Translation（Unsupervised Statistical Machine Translation）</news:title>
   <news:publication_date>2026-06-09T17:20:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698831</loc>
  <lastmod>2026-06-09T16:29:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepHunterによるDNN欠陥検出の実務的意義（DeepHunter: Hunting Deep Neural Network Defects via Coverage-Guided Fuzzing）</news:title>
   <news:publication_date>2026-06-09T16:29:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698829</loc>
  <lastmod>2026-06-09T16:28:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰的世界モデルが方策進化を促進する（Recurrent World Models Facilitate Policy Evolution）</news:title>
   <news:publication_date>2026-06-09T16:28:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698827</loc>
  <lastmod>2026-06-09T16:28:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内視鏡映像におけるポリープ検出の効率的手法（An Efficient Approach for Polyps Detection in Endoscopic Videos Based on Faster R-CNN）</news:title>
   <news:publication_date>2026-06-09T16:28:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698825</loc>
  <lastmod>2026-06-09T16:28:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>β-Ga2O3におけるドナーと深いアクセプターの実態（Donors and Deep Acceptors in β-Ga2O3）</news:title>
   <news:publication_date>2026-06-09T16:28:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698823</loc>
  <lastmod>2026-06-09T16:27:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチアドバーサリアル領域適応（Multi-Adversarial Domain Adaptation）</news:title>
   <news:publication_date>2026-06-09T16:27:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698821</loc>
  <lastmod>2026-06-09T16:27:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>t-指数メモリネットワークによる質問応答機（t-Exponential Memory Networks for Question-Answering Machines）</news:title>
   <news:publication_date>2026-06-09T16:27:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698819</loc>
  <lastmod>2026-06-09T16:27:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>優先度付き深層ハッシングの実務的示唆（Deep Priority Hashing）</news:title>
   <news:publication_date>2026-06-09T16:27:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698817</loc>
  <lastmod>2026-06-09T15:36:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフから深い木へ変換する再帰型ニューラルネットワーク（GRAPH-BASED DEEP-TREE RECURSIVE NEURAL NETWORK (DTRNN) FOR TEXT CLASSIFICATION）</news:title>
   <news:publication_date>2026-06-09T15:36:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698815</loc>
  <lastmod>2026-06-09T15:36:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成確率平均勾配法（Compositional Stochastic Average Gradient for Machine Learning and Related Applications）</news:title>
   <news:publication_date>2026-06-09T15:36:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698813</loc>
  <lastmod>2026-06-09T15:35:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム言語モデルによる言語の構造生成の臨界現象（Random Language Model）</news:title>
   <news:publication_date>2026-06-09T15:35:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698811</loc>
  <lastmod>2026-06-09T15:35:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動きの顕著性に導かれる教師なし映像物体分割（Unsupervised Video Object Segmentation using Motion Saliency-Guided Spatio-Temporal Propagation）</news:title>
   <news:publication_date>2026-06-09T15:35:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698809</loc>
  <lastmod>2026-06-09T15:35:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepPINKによるDNNの再現性ある特徴選択（DeepPINK: reproducible feature selection in deep neural networks）</news:title>
   <news:publication_date>2026-06-09T15:35:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698807</loc>
  <lastmod>2026-06-09T15:35:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SN 2012auにおけるパルサー風天体の証拠（Evidence for a pulsar wind nebula in the Type Ib-peculiar supernova SN 2012au）</news:title>
   <news:publication_date>2026-06-09T15:35:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698805</loc>
  <lastmod>2026-06-09T15:34:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MUSEによる超微光放射線銀河の分光同定（MUSE Spectroscopic Identiﬁcations of Ultra-Faint Emission Line Galaxies with MUV ∼-15）</news:title>
   <news:publication_date>2026-06-09T15:34:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698803</loc>
  <lastmod>2026-06-09T14:43:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事実に直行する知識ベース検索の学習（Straight to the Facts: Learning Knowledge Base Retrieval for Factual Visual Question Answering）</news:title>
   <news:publication_date>2026-06-09T14:43:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698801</loc>
  <lastmod>2026-06-09T14:43:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マッチングに基づく動画物体セグメンテーションの要点解説（VideoMatch: Matching based Video Object Segmentation）</news:title>
   <news:publication_date>2026-06-09T14:43:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698799</loc>
  <lastmod>2026-06-09T14:42:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュートリノ親和性アルプトン様暗黒物質（Neutrinophilic Axion-Like Dark Matter）</news:title>
   <news:publication_date>2026-06-09T14:42:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698797</loc>
  <lastmod>2026-06-09T14:42:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミリ波におけるビームスイープ高速化（Accelerating Beam Sweeping in mmWave Standalone 5G New Radios using Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-06-09T14:42:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698795</loc>
  <lastmod>2026-06-09T14:41:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Text2Scene: 文章から構成的なシーンを生成する方法（Text2Scene: Generating Compositional Scenes from Textual Descriptions）</news:title>
   <news:publication_date>2026-06-09T14:41:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698793</loc>
  <lastmod>2026-06-09T14:41:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノード埋め込みに対するグラフ汚染型の敵対的攻撃の脆弱性（Adversarial Attacks on Node Embeddings via Graph Poisoning）</news:title>
   <news:publication_date>2026-06-09T14:41:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698791</loc>
  <lastmod>2026-06-09T14:41:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間変化する有向ネットワーク上の分散非凸制約最適化（Distributed Nonconvex Constrained Optimization over Time-Varying Digraphs）</news:title>
   <news:publication_date>2026-06-09T14:41:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698789</loc>
  <lastmod>2026-06-09T13:50:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多体量子もつれのトモグラフィで見る量子シミュレータの地図（Multipartite-Entanglement Tomography of a Quantum Simulator）</news:title>
   <news:publication_date>2026-06-09T13:50:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698787</loc>
  <lastmod>2026-06-09T13:48:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子空間グラフ畳み込みと頂点顕著性によるグラフ分類（Graph Convolutional Neural Networks based on Quantum Vertex Saliency）</news:title>
   <news:publication_date>2026-06-09T13:48:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698785</loc>
  <lastmod>2026-06-09T13:48:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河がAGB星を気にする理由とクラスター内惑星状星雲の示唆（Central Stars of Planetary Nebulae in Galactic Open Clusters: Providing additional data for the White Dwarf Initial-to-Final-Mass Relation）</news:title>
   <news:publication_date>2026-06-09T13:48:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698783</loc>
  <lastmod>2026-06-09T13:48:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子体系向け深層学習ツールボックス SchNetPack（SchNetPack: A Deep Learning Toolbox For Atomistic Systems）</news:title>
   <news:publication_date>2026-06-09T13:48:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698781</loc>
  <lastmod>2026-06-09T13:47:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>キャリア経路最適化の新基準：マルチ基準効用学習によるJobComposer（JobComposer: Career Path Optimization via Multicriteria Utility Learning）</news:title>
   <news:publication_date>2026-06-09T13:47:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698779</loc>
  <lastmod>2026-06-09T13:47:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カイ二乗検定ニューラルネットワーク（Chi-Square Test Neural Network）</news:title>
   <news:publication_date>2026-06-09T13:47:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698777</loc>
  <lastmod>2026-06-09T13:47:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数注意機構を持つ新しい系列ニューラルモデルによる語義曖昧性解消（A Novel Neural Sequence Model with Multiple Attentions for Word Sense Disambiguation）</news:title>
   <news:publication_date>2026-06-09T13:47:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698766</loc>
  <lastmod>2026-06-09T12:56:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>形状制約を用いた関数推定の改善（Shape-Enforcing Operators for Generic Point and Interval Estimators of Functions）</news:title>
   <news:publication_date>2026-06-09T12:56:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698764</loc>
  <lastmod>2026-06-09T12:55:45Z</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支援によるLDPC符号化DCO-OFDMのクリッピング歪み低減（A Neural Network Aided Approach for LDPC Coded DCO-OFDM with Clipping Distortion）</news:title>
   <news:publication_date>2026-06-09T12:55:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698762</loc>
  <lastmod>2026-06-09T12:55:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己教師型除外分類器のアンサンブルによる分布外検知（Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-out Classiﬁers）</news:title>
   <news:publication_date>2026-06-09T12:55:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698760</loc>
  <lastmod>2026-06-09T12:54:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的な画像記述子を用いた効率的な自己位置推定（Leveraging Deep Visual Descriptors for Hierarchical Efficient Localization）</news:title>
   <news:publication_date>2026-06-09T12:54:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698758</loc>
  <lastmod>2026-06-09T12:54:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>射影モデルに基づくパラメータ転移型極限学習機 (Parameter Transfer Extreme Learning Machine based on Projective Model)</news:title>
   <news:publication_date>2026-06-09T12:54:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698756</loc>
  <lastmod>2026-06-09T12:54:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフレイアウトの美的判別器（Aesthetic Discrimination of Graph Layouts）</news:title>
   <news:publication_date>2026-06-09T12:54:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698754</loc>
  <lastmod>2026-06-09T12:53:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン特化型CNNをFPGAで効率化する手法（Towards Efficient Convolutional Neural Network for Domain-Specific Applications on FPGA）</news:title>
   <news:publication_date>2026-06-09T12:53:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698752</loc>
  <lastmod>2026-06-09T12:02:17Z</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と全結合ネットワークの近似等価性（Equivalence of Approximation by Convolutional Neural Networks and Fully-Connected Networks）</news:title>
   <news:publication_date>2026-06-09T12:02:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698750</loc>
  <lastmod>2026-06-09T12:02:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声から話者横断で「舌・口の動き」を推定する方法（IMPROVING GENERALIZATION OF VOCAL TRACT FEATURE RECONSTRUCTION）</news:title>
   <news:publication_date>2026-06-09T12:02:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698748</loc>
  <lastmod>2026-06-09T12:01:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元データの高速かつバランスのとれたクラスタリング手法（Faster Balanced Clusterings in High Dimension⋆）</news:title>
   <news:publication_date>2026-06-09T12:01:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698746</loc>
  <lastmod>2026-06-09T12:00:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バングラ語ナンバープレート認識におけるCNNの応用（Bangla License Plate Recognition Using Convolutional Neural Networks (CNN)）</news:title>
   <news:publication_date>2026-06-09T12:00:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698744</loc>
  <lastmod>2026-06-09T12:00:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セグメンテーションフリーの合成n-グラム埋め込み（Segmentation-free Compositional n-gram Embedding）</news:title>
   <news:publication_date>2026-06-09T12:00:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698742</loc>
  <lastmod>2026-06-09T12:00:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IntelとAMDマイクロアーキテクチャ向け命令ストリームスループット自動予測（Automated Instruction Stream Throughput Prediction for Intel and AMD Microarchitectures）</news:title>
   <news:publication_date>2026-06-09T12:00:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698740</loc>
  <lastmod>2026-06-09T12:00:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最近のSTAR実験による偏極グルーオン分布の制約（Recent STAR Measurements to Constrain the Polarized Gluon Distribution Function of the Proton）</news:title>
   <news:publication_date>2026-06-09T12:00:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698738</loc>
  <lastmod>2026-06-09T11:08:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パリティ問合せによる二値分類（Parity Queries for Binary Classification）</news:title>
   <news:publication_date>2026-06-09T11:08:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698736</loc>
  <lastmod>2026-06-09T11:08:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>上位成績者を抑制する保守的損失（Penalizing Top Performers: Conservative Loss for Semantic Segmentation Adaptation）</news:title>
   <news:publication_date>2026-06-09T11:08:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698734</loc>
  <lastmod>2026-06-09T11:07:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像の再構成：深層学習と最短経路問題の統合（Image Reassembly Combining Deep Learning and Shortest Path Problem）</news:title>
   <news:publication_date>2026-06-09T11:07:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698732</loc>
  <lastmod>2026-06-09T11:06:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔動画の改ざん検出を軽量に実現するMesoNet（MesoNet: a Compact Facial Video Forgery Detection Network）</news:title>
   <news:publication_date>2026-06-09T11:06:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698730</loc>
  <lastmod>2026-06-09T11:06:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セルラー網におけるエッジキャッシュでのプライベート情報取得（Private Information Retrieval From a Cellular Network With Caching at the Edge）</news:title>
   <news:publication_date>2026-06-09T11:06:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698728</loc>
  <lastmod>2026-06-09T11:06:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SNMP-MIBデータを用いたネットワーク異常検知の実践的解説（Exploiting SNMP-MIB Data to Detect Network Anomalies using Machine Learning Techniques）</news:title>
   <news:publication_date>2026-06-09T11:06:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698726</loc>
  <lastmod>2026-06-09T11:05:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動鳥鳴き声認識の現実適用性（Automated bird sound recognition in realistic settings）</news:title>
   <news:publication_date>2026-06-09T11:05:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698724</loc>
  <lastmod>2026-06-09T10:15:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連星にあるポストAGB星が示すもの（Binary post-AGB stars as tracers of stellar evolution）</news:title>
   <news:publication_date>2026-06-09T10:15:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698722</loc>
  <lastmod>2026-06-09T10:14:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手書き文字のスタイル評価とベンチマーク（Handwriting styles: benchmarks and evaluation metrics）</news:title>
   <news:publication_date>2026-06-09T10:14:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698720</loc>
  <lastmod>2026-06-09T10:14:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数ターゲットを持つ教師なしドメイン適応（Multi-target Unsupervised Domain Adaptation without Exactly Shared Categories）</news:title>
   <news:publication_date>2026-06-09T10:14:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698718</loc>
  <lastmod>2026-06-09T10:13:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的ニューラルネットワーク事前分布を用いた制約付き合理的意思決定（Bounded Rational Decision-Making with Adaptive Neural Network Priors）</news:title>
   <news:publication_date>2026-06-09T10:13:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698716</loc>
  <lastmod>2026-06-09T10:13:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチ正規化における正則化の理解（TOWARDS UNDERSTANDING REGULARIZATION IN BATCH NORMALIZATION）</news:title>
   <news:publication_date>2026-06-09T10:13:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698714</loc>
  <lastmod>2026-06-09T10:13:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューロンの増殖と自食に基づく可変ニューラルネットワーク（Metabolize Neural Network）</news:title>
   <news:publication_date>2026-06-09T10:13:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698712</loc>
  <lastmod>2026-06-09T10:13:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情量化のための再帰型ニューラルネットワーク（A Recurrent Neural Network for Sentiment Quantification）</news:title>
   <news:publication_date>2026-06-09T10:13:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698710</loc>
  <lastmod>2026-06-09T09:21:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰を導入した深層学習フレームワークの表現力向上（Improving the Expressiveness of Deep Learning Frameworks with Recursion）</news:title>
   <news:publication_date>2026-06-09T09:21:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698708</loc>
  <lastmod>2026-06-09T09:21:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線画像伝送のための深層結合ソース・チャネル符号化（Deep Joint Source-Channel Coding for Wireless Image Transmission）</news:title>
   <news:publication_date>2026-06-09T09:21:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698706</loc>
  <lastmod>2026-06-09T09:20:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元可変インデックス係数分位回帰モデル（High-dimensional varying index coefficient quantile regression model）</news:title>
   <news:publication_date>2026-06-09T09:20:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698704</loc>
  <lastmod>2026-06-09T09:19:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>疎な言語表現のための点ごとのHSIC（Pointwise HSIC: A Linear-Time Kernelized Co-occurrence Norm for Sparse Linguistic Expressions）</news:title>
   <news:publication_date>2026-06-09T09:19:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698702</loc>
  <lastmod>2026-06-09T09:19:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fe/GeTe(111) ヘテロ構造が拓く強誘電ラシュバ半導体志向スピントロニクス（Fe/GeTe(111) heterostructures as an avenue towards &amp;#039;ferroelectric Rashba semiconductors&amp;#039; - based spintronics）</news:title>
   <news:publication_date>2026-06-09T09:19:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698700</loc>
  <lastmod>2026-06-09T09:19:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル群衆ソースサービスの時空間可用性予測フレームワーク（A Deep Learning Spatiotemporal Prediction Framework for Mobile Crowdsourced Services）</news:title>
   <news:publication_date>2026-06-09T09:19:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698698</loc>
  <lastmod>2026-06-09T09:18:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>（概要解説）(2 + 1)-次元KPZ方程式の解の構成（CONSTRUCTING A SOLUTION OF THE (2 + 1)-DIMENSIONAL KPZ EQUATION）</news:title>
   <news:publication_date>2026-06-09T09:18:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698696</loc>
  <lastmod>2026-06-09T08:27:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Texar：モジュール化された汎用テキスト生成ツールキット（Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation）</news:title>
   <news:publication_date>2026-06-09T08:27:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698694</loc>
  <lastmod>2026-06-09T08:26:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識ベースとテキストを早期融合して問に答える（Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text）</news:title>
   <news:publication_date>2026-06-09T08:26:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698692</loc>
  <lastmod>2026-06-09T08:26:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lipschitzネットワークと分布的ロバスト性（Lipschitz Networks and Distributional Robustness）</news:title>
   <news:publication_date>2026-06-09T08:26:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698690</loc>
  <lastmod>2026-06-09T08:25:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的ビデオ理解の要点と経営判断への示唆（Hierarchical Video Understanding）</news:title>
   <news:publication_date>2026-06-09T08:25:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698688</loc>
  <lastmod>2026-06-09T08:25:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一ソースから学習を移す技術：敵対的目的と拡張による強化学習の転移（Transferring Deep Reinforcement Learning with Adversarial Objective and Augmentation）</news:title>
   <news:publication_date>2026-06-09T08:25:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698686</loc>
  <lastmod>2026-06-09T08:25:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>煙の精密分割を可能にした二経路FCNと合成データ生成（Two-Path Fully Convolutional Networks for Smoke Segmentation）</news:title>
   <news:publication_date>2026-06-09T08:25:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698684</loc>
  <lastmod>2026-06-09T08:25:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Sequence-to-Action: End-to-End Semantic Graph Generation for Semantic Parsing（Sequence-to-Action: End-to-End Semantic Graph Generation for Semantic Parsing）</news:title>
   <news:publication_date>2026-06-09T08:25:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698682</loc>
  <lastmod>2026-06-09T07:33:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間・分光融合における深層学習とモデルベースの統合（Spatial-Spectral Fusion by Combining Deep Learning and Variation Model）</news:title>
   <news:publication_date>2026-06-09T07:33:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698680</loc>
  <lastmod>2026-06-09T07:33:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高頻度トランジェント調査による光度曲線カタログの編纂と特性評価（The High Cadence Transient Survey (HiTS) Compilation and characterization of light–curve catalogs）</news:title>
   <news:publication_date>2026-06-09T07:33:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698678</loc>
  <lastmod>2026-06-09T07:33:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的結合損失で変わる感情・性別認識──終端から学ぶマルチモーダル認識の実務的意味 (Dynamic Joint Loss Weights for End-to-End Multimodal Emotion and Gender Recognition)</news:title>
   <news:publication_date>2026-06-09T07:33:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698676</loc>
  <lastmod>2026-06-09T07:32:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HASP: モバイル向け高性能適応音声セキュリティ強化（HASP: A High-Performance Adaptive Mobile Security Enhancement Against Malicious Speech Recognition）</news:title>
   <news:publication_date>2026-06-09T07:32:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698674</loc>
  <lastmod>2026-06-09T07:32:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一時系列観測に基づくデータ依存因果効果の頑健推定（Robust Estimation of Data-Dependent Causal Effects based on Observing a Single Time-Series）</news:title>
   <news:publication_date>2026-06-09T07:32:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698672</loc>
  <lastmod>2026-06-09T07:32:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTDots：スマート環境向けデジタルフォレンジクス枠組み（IoTDots: A Digital Forensics Framework for Smart Environments）</news:title>
   <news:publication_date>2026-06-09T07:32:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698670</loc>
  <lastmod>2026-06-09T07:31:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>政治家の発言から党派とイデオロギーを分類する手法（“Read My Lips”: Using Automatic Text Analysis to Classify Politicians by Party and Ideology）</news:title>
   <news:publication_date>2026-06-09T07:31:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698668</loc>
  <lastmod>2026-06-09T06:40:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>InteriorNetによる室内シーン合成の大規模化と写実性向上（InteriorNet: Mega-scale Multi-sensor Photo-realistic Indoor Scenes Dataset）</news:title>
   <news:publication_date>2026-06-09T06:40:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698666</loc>
  <lastmod>2026-06-09T06:40:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子カルテ向け大規模QAコーパスemrQAの構築（emrQA: A Large Corpus for Question Answering on Electronic Medical Records）</news:title>
   <news:publication_date>2026-06-09T06:40:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698664</loc>
  <lastmod>2026-06-09T06:40:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NTUA-SLP による感情欠落語彙の推定手法 ― 転移学習とアンサンブルの実践（Ensemble of Neural Transfer Methods for Implicit Emotion Classification）</news:title>
   <news:publication_date>2026-06-09T06:40:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698662</loc>
  <lastmod>2026-06-09T06:39:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グループ笑顔強度推定のためのグローバルアライメントカーネル（A Global Alignment Kernel based Approach for Group-level Happiness Intensity Estimation）</news:title>
   <news:publication_date>2026-06-09T06:39:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698660</loc>
  <lastmod>2026-06-09T06:39:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FRIBとGW170817キロノバの示唆（FRIB and the GW170817 Kilonova）</news:title>
   <news:publication_date>2026-06-09T06:39:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698658</loc>
  <lastmod>2026-06-09T06:39:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク上の分散最適化で最適率を達成する二重アプローチ（A Dual Approach for Optimal Algorithms in Distributed Optimization over Networks）</news:title>
   <news:publication_date>2026-06-09T06:39:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698656</loc>
  <lastmod>2026-06-09T06:39:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小割引報酬によるHamilton–Jacobi到達可能集合の新定式化（A Minimum Discounted Reward Hamilton-Jacobi Formulation for Computing Reachable Sets）</news:title>
   <news:publication_date>2026-06-09T06:39:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698654</loc>
  <lastmod>2026-06-09T05:47:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層構造化自己注意による遠隔教師付き関係抽出（Multi-Level Structured Self-Attentions for Distantly Supervised Relation Extraction）</news:title>
   <news:publication_date>2026-06-09T05:47:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698652</loc>
  <lastmod>2026-06-09T05:47:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンプライアント運動の分割と連結（Segmenting and Sequencing of Compliant Motions）</news:title>
   <news:publication_date>2026-06-09T05:47:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698650</loc>
  <lastmod>2026-06-09T05:47:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗号通貨の時系列における臨界転移の位相幾何学的認識（TOPOLOGICAL RECOGNITION OF CRITICAL TRANSITIONS IN TIME SERIES OF CRYPTOCURRENCIES）</news:title>
   <news:publication_date>2026-06-09T05:47:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698648</loc>
  <lastmod>2026-06-09T05:46:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈パッチに基づく顔ハリュシネーション：しきい値付き局所制約表現と再現学習（Context-Patch Face Hallucination Based on Thresholding Locality-constrained Representation and Reproducing Learning）</news:title>
   <news:publication_date>2026-06-09T05:46:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698646</loc>
  <lastmod>2026-06-09T05:46:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習型カーディナリティ推定（Learned Cardinalities: Estimating Correlated Joins with Deep Learning）</news:title>
   <news:publication_date>2026-06-09T05:46:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698644</loc>
  <lastmod>2026-06-09T05:46:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース潜在構造による動的計算グラフの実現（Towards Dynamic Computation Graphs via Sparse Latent Structure）</news:title>
   <news:publication_date>2026-06-09T05:46:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698642</loc>
  <lastmod>2026-06-09T05:46:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効果的なウェブサービス開発のためのオンライン評価（Online Evaluation for Effective Web Service Development）</news:title>
   <news:publication_date>2026-06-09T05:46:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698640</loc>
  <lastmod>2026-06-09T04:54:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小記述長（MDL）符号はなぜ「臨界」なのか（Minimum Description Length codes are critical）</news:title>
   <news:publication_date>2026-06-09T04:54:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698638</loc>
  <lastmod>2026-06-09T04:54:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>まばらな視線点からの注目予測学習（Learning Saliency Prediction From Sparse Fixation Pixel Map）</news:title>
   <news:publication_date>2026-06-09T04:54:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698636</loc>
  <lastmod>2026-06-09T04:54:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>認知行動療法に基づくメンタルヘルス概念の言語理解に向けた深層学習（Deep learning for language understanding of mental health concepts derived from Cognitive Behavioural Therapy）</news:title>
   <news:publication_date>2026-06-09T04:54:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698634</loc>
  <lastmod>2026-06-09T04:54:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Intersection over Unionがサブモジュラ関数でないことの示唆（INTERSECTION OVER UNION IS NOT A SUBMODULAR FUNCTION）</news:title>
   <news:publication_date>2026-06-09T04:54:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698632</loc>
  <lastmod>2026-06-09T04:54:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有意な変化による分類器の騙し方（Adversarial Attack Type I: Cheat Classifiers by Significant Changes）</news:title>
   <news:publication_date>2026-06-09T04:54:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698630</loc>
  <lastmod>2026-06-09T04:53:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルを盗まれたか？ 深層ニューラルネットワークのウォーターマーク回避攻撃（Have You Stolen My Model? Evasion Attacks Against Deep Neural Network Watermarking Techniques）</news:title>
   <news:publication_date>2026-06-09T04:53:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698628</loc>
  <lastmod>2026-06-09T04:53:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UKP-Athene: 複数文のテキスト含意を用いた主張検証（UKP-Athene: Multi-Sentence Textual Entailment for Claim Verification）</news:title>
   <news:publication_date>2026-06-09T04:53:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698626</loc>
  <lastmod>2026-06-09T04:02:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DenseNetを用いたカメラモデル識別と後処理検出（Application of DenseNet in Camera Model Identification and Post-processing Detection）</news:title>
   <news:publication_date>2026-06-09T04:02:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698624</loc>
  <lastmod>2026-06-09T03:53:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Prof. CIによるTDD教育の自動化（Prof. CI: Employing Continuous Integration Services and Github Workflows to Teach Test-driven Development）</news:title>
   <news:publication_date>2026-06-09T03:53:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698622</loc>
  <lastmod>2026-06-09T03:53:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チェレンコフ望遠鏡アレイのリアルタイム分散ストリーム解析（Distributed Real-Time Data Stream Analysis for CTA）</news:title>
   <news:publication_date>2026-06-09T03:53:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698620</loc>
  <lastmod>2026-06-09T03:52:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視線スキャンパス予測のためのPathGAN（PathGAN: Visual Scanpath Prediction with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-09T03:52:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698618</loc>
  <lastmod>2026-06-09T03:52:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集合脳を志向するViewpointS（ViewpointS: towards a Collective Brain）</news:title>
   <news:publication_date>2026-06-09T03:52:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698616</loc>
  <lastmod>2026-06-09T03:52:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セマンティック情報G理論と論理的ベイズ推論（Semantic Information G Theory and Logical Bayesian Inference for Machine Learning）</news:title>
   <news:publication_date>2026-06-09T03:52:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698614</loc>
  <lastmod>2026-06-09T03:51:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼画像からの物体姿勢推定：マルチビュー鍵点対応による接近戦（Object Pose Estimation from Monocular Image using Multi-View Keypoint Correspondence）</news:title>
   <news:publication_date>2026-06-09T03:51:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698612</loc>
  <lastmod>2026-06-09T03:00:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドローン群ロボットの視覚駆動集団飛行学習（Learning Vision-based Cohesive Flight in Drone Swarms）</news:title>
   <news:publication_date>2026-06-09T03:00:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698610</loc>
  <lastmod>2026-06-09T02:59:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インタラクティブな世界でのコミュニケーションの自発的出現（Emergence of Communication in an Interactive World with Consistent Speakers）</news:title>
   <news:publication_date>2026-06-09T02:59:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698608</loc>
  <lastmod>2026-06-09T02:59:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>火星探査機の熱消費を予測する機械学習（Machine learning for predicting thermal power consumption of the Mars Express Spacecraft）</news:title>
   <news:publication_date>2026-06-09T02:59:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698606</loc>
  <lastmod>2026-06-09T02:58:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声事象分類における人間知覚の深層学習（Deep Learning of Human Perception in Audio Event Classification）</news:title>
   <news:publication_date>2026-06-09T02:58:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698604</loc>
  <lastmod>2026-06-09T02:58:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスドメイン感情分類のための適応的半教師あり学習（Adaptive Semi-supervised Learning for Cross-domain Sentiment Classification）</news:title>
   <news:publication_date>2026-06-09T02:58:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698602</loc>
  <lastmod>2026-06-09T02:58:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Flatland：軽量な一人称2次元強化学習環境（Flatland: a Lightweight First-Person 2-D Environment for Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-09T02:58:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698600</loc>
  <lastmod>2026-06-09T02:57:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不可聴エコーを用いた深層室内認識（Deep Room Recognition Using Inaudible Echos）</news:title>
   <news:publication_date>2026-06-09T02:57:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698598</loc>
  <lastmod>2026-06-09T02:06:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化された機械学習サービス（Automated Machine Learning Service）</news:title>
   <news:publication_date>2026-06-09T02:06:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698596</loc>
  <lastmod>2026-06-09T02:05:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非パラメトリック形状事前分布を扱うPseudo-marginal MCMCによる画像セグメンテーション（Image Segmentation with Pseudo-marginal MCMC）</news:title>
   <news:publication_date>2026-06-09T02:05:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698594</loc>
  <lastmod>2026-06-09T02:05:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報源の信頼性指標が持つ逆手利用のリスク（Belittling the Source: Trustworthiness Indicators to Obfuscate Fake News on the Web）</news:title>
   <news:publication_date>2026-06-09T02:05:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698592</loc>
  <lastmod>2026-06-09T02:05:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>YouTube-VOS によるシーケンス・トゥ・シーケンス動画物体分割（YouTube-VOS: Sequence-to-Sequence Video Object Segmentation）</news:title>
   <news:publication_date>2026-06-09T02:05:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698590</loc>
  <lastmod>2026-06-09T02:04:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペアなし学習での単一画像超解像（Unsupervised Image Super-Resolution using Cycle-in-Cycle Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-09T02:04:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698588</loc>
  <lastmod>2026-06-09T02:04:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>区分線形ユニット（PLU）活性化関数（PLU: The Piecewise Linear Unit Activation Function）</news:title>
   <news:publication_date>2026-06-09T02:04:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698586</loc>
  <lastmod>2026-06-09T02:04:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙のウェブをβ-skeletonで読み解く（β-Skeleton Analysis of the Cosmic Web）</news:title>
   <news:publication_date>2026-06-09T02:04:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698584</loc>
  <lastmod>2026-06-09T01:13:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モールス・サード定理とルジンN性のSobolev空間における新合成結果（Morse–Sard theorem and Luzin N-property: a new synthesis result for Sobolev spaces）</news:title>
   <news:publication_date>2026-06-09T01:13:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698582</loc>
  <lastmod>2026-06-09T01:12:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的に学習するビュー不変表現による視点横断アクション認識（Hierarchically Learned View-Invariant Representations for Cross-View Action Recognition）</news:title>
   <news:publication_date>2026-06-09T01:12:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698580</loc>
  <lastmod>2026-06-09T01:12:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的シーンにおける3D LiDARデータのセマンティックセグメンテーション（Semantic Segmentation of 3D LiDAR Data in Dynamic Scene Using Semi-supervised Learning）</news:title>
   <news:publication_date>2026-06-09T01:12:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698578</loc>
  <lastmod>2026-06-09T01:12:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イベント境界がエゴセントリック活動認識に果たす役割（On the Role of Event Boundaries in Egocentric Activity Recognition from Photostreams）</news:title>
   <news:publication_date>2026-06-09T01:12:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698576</loc>
  <lastmod>2026-06-09T01:11:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>記事内部構造で掴む上位語検出（Hypernyms Through Intra-Article Organization in Wikipedia）</news:title>
   <news:publication_date>2026-06-09T01:11:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698574</loc>
  <lastmod>2026-06-09T01:11:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Tsallisエントロピー正則化下でのブートストラップQアンサンブルによる深い強化学習の効率的探索（Effective Exploration for Deep Reinforcement Learning via Bootstrapped Q-Ensembles under Tsallis Entropy Regularization）</news:title>
   <news:publication_date>2026-06-09T01:11:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698572</loc>
  <lastmod>2026-06-09T01:11:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>談話における主題的一貫性の無教師的評価（Modeling Topical Coherence in Discourse without Supervision）</news:title>
   <news:publication_date>2026-06-09T01:11:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698570</loc>
  <lastmod>2026-06-09T00:20:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MANTIS：効率的なMR T2マッピングを実現するモデル強化ニューラルネットワーク（MANTIS: Model-Augmented Neural neTwork with Incoherent k-space Sampling for efficient MR T2 mapping）</news:title>
   <news:publication_date>2026-06-09T00:20:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698568</loc>
  <lastmod>2026-06-09T00:19:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Atariゲーム間の視覚転移と競合強化学習（Visual Transfer between Atari Games using Competitive Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-09T00:19:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698566</loc>
  <lastmod>2026-06-09T00:19:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>屋外環境で自律航行を学ぶMAVNet（Learning to Navigate Autonomously in Outdoor Environments : MAVNet）</news:title>
   <news:publication_date>2026-06-09T00:19:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698564</loc>
  <lastmod>2026-06-09T00:18:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集合行列因子分解によるコールドスタート推薦（Cold-start recommendations in Collective Matrix Factorization）</news:title>
   <news:publication_date>2026-06-09T00:18:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698562</loc>
  <lastmod>2026-06-09T00:18:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>油圧マニピュレータにおけるデモ学習法（Learning from Demonstration for Hydraulic Manipulators）</news:title>
   <news:publication_date>2026-06-09T00:18:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698560</loc>
  <lastmod>2026-06-09T00:18:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音楽における基本周波数推定のマルチタスク学習（Multitask Learning for Fundamental Frequency Estimation in Music）</news:title>
   <news:publication_date>2026-06-09T00:18:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698558</loc>
  <lastmod>2026-06-09T00:18:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Zero-shot User Intent Detection via Capsule Neural Networks（Zero-shot User Intent Detection via Capsule Neural Networks）</news:title>
   <news:publication_date>2026-06-09T00:18:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698556</loc>
  <lastmod>2026-06-08T23:26:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教育現場でのソーシャルネットワーク分析実践ガイド（Practitioner’s guide to social network analysis）</news:title>
   <news:publication_date>2026-06-08T23:26:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698554</loc>
  <lastmod>2026-06-08T23:17:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語を用いた人物検索と深層強化学習（Natural Language Person Search Using Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-08T23:17:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698552</loc>
  <lastmod>2026-06-08T23:17:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>神経データにおける状態変化の逐次検出（Sequential Detection of Regime Changes in Neural Data）</news:title>
   <news:publication_date>2026-06-08T23:17:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698550</loc>
  <lastmod>2026-06-08T23:17:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低リソース機械翻訳における単純転移学習の実践（Trivial Transfer Learning for Low-Resource Neural Machine Translation）</news:title>
   <news:publication_date>2026-06-08T23:17:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698548</loc>
  <lastmod>2026-06-08T23:16:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バングラ語自動画像キャプション生成の実践（Chittron: An Automatic Bangla Image Captioning）</news:title>
   <news:publication_date>2026-06-08T23:16:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698546</loc>
  <lastmod>2026-06-08T23:16:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アマゾン熱帯雨林の土地パターン検出（Identifying Land Patterns from Satellite Imagery in Amazon Rainforest using Deep Learning）</news:title>
   <news:publication_date>2026-06-08T23:16:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698544</loc>
  <lastmod>2026-06-08T23:15:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>年齢差を超える顔認識のための表現分離と写実的世代交差合成（Look Across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition）</news:title>
   <news:publication_date>2026-06-08T23:15:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698542</loc>
  <lastmod>2026-06-08T22:24:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次ツイスト分布とハドロン性CP変動の関係（Relating hadronic CP-violation to higher-twist distributions）</news:title>
   <news:publication_date>2026-06-08T22:24:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698540</loc>
  <lastmod>2026-06-08T22:24:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中国語ピンイン支援IME — 入力していない文字を補完する手法 (Chinese Pinyin Aided IME, Input What You Have Not Keystroked Yet)</news:title>
   <news:publication_date>2026-06-08T22:24:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698538</loc>
  <lastmod>2026-06-08T22:24:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車車間通信における非協力的周波数資源割当のゲーム理論的解析（Learning to Entangle Radio Resources in Vehicular Communications: An Oblivious Game-Theoretic Perspective）</news:title>
   <news:publication_date>2026-06-08T22:24:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698536</loc>
  <lastmod>2026-06-08T22:22:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑ネットワークにおける知識合意と学習の役割（Knowledge Consensus in complex networks: the role of learning）</news:title>
   <news:publication_date>2026-06-08T22:22:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698534</loc>
  <lastmod>2026-06-08T22:22:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手作業特徴量と深層ニューラルネットワークによるOCT画像分類の比較（A Comparison of Handcrafted and Deep Neural Network Feature Extraction for Classifying Optical Coherence Tomography (OCT) Images）</news:title>
   <news:publication_date>2026-06-08T22:22:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698532</loc>
  <lastmod>2026-06-08T22:22:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数データ源を統合する拡張結合隠れマルコフモデルによる株価予測（Enhancing Stock Market Prediction with Extended Coupled Hidden Markov Model over Multi-Sourced Data）</news:title>
   <news:publication_date>2026-06-08T22:22:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698530</loc>
  <lastmod>2026-06-08T22:22:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細粒度分類のための探索学習（Learning to Navigate for Fine-grained Classification）</news:title>
   <news:publication_date>2026-06-08T22:22:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698528</loc>
  <lastmod>2026-06-08T21:31:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱い教師ありニューラル文書分類（Weakly-Supervised Neural Text Classification）</news:title>
   <news:publication_date>2026-06-08T21:31:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698526</loc>
  <lastmod>2026-06-08T21:30:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現論に基づく塑性流動の機械学習モデル（Machine learning models of plastic flow based on representation theory）</news:title>
   <news:publication_date>2026-06-08T21:30:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698524</loc>
  <lastmod>2026-06-08T21:30:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期動画の間を自然に埋める確率的手法（Stochastic Dynamics for Video Inﬁlling）</news:title>
   <news:publication_date>2026-06-08T21:30:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698522</loc>
  <lastmod>2026-06-08T21:30:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床試験における文脈バンディットによる意思決定支援（A Contextual-bandit-based Approach for Informed Decision-making in Clinical Trials）</news:title>
   <news:publication_date>2026-06-08T21:30:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698520</loc>
  <lastmod>2026-06-08T21:30:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集合住宅地下駐車場における小型自律走行車による監視システム（Car Monitoring System in Apartment Garages）</news:title>
   <news:publication_date>2026-06-08T21:30:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698518</loc>
  <lastmod>2026-06-08T21:29:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習を用いたネットワーク侵入検知の手法（Machine Learning Methods for Network Intrusion Detection）</news:title>
   <news:publication_date>2026-06-08T21:29:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698516</loc>
  <lastmod>2026-06-08T21:29:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多言語自己注意型翻訳モデルにおけるパラメータ共有手法（Parameter Sharing Methods for Multilingual Self-Attentional Translation Models）</news:title>
   <news:publication_date>2026-06-08T21:29:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698514</loc>
  <lastmod>2026-06-08T20:38:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短尺動画における大規模行動認識（ACTIVITY RECOGNITION ON A LARGE SCALE IN SHORT VIDEOS - MOMENTS IN TIME DATASET）</news:title>
   <news:publication_date>2026-06-08T20:38:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698512</loc>
  <lastmod>2026-06-08T20:38:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートシティ向け低コストIoTと機械学習による騒音分類（A Machine Learning Driven IoT Solution for Noise Classification in Smart Cities）</news:title>
   <news:publication_date>2026-06-08T20:38:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698510</loc>
  <lastmod>2026-06-08T20:37:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>睡眠ステージ分類：分散アプローチのスケーラビリティ評価（Sleep Stage Classification: Scalability Evaluations of Distributed Approaches）</news:title>
   <news:publication_date>2026-06-08T20:37:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698508</loc>
  <lastmod>2026-06-08T20:37:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VoxSegNet：ボクセルベースの3D部分分割を可能にする畳み込みネットワーク (VoxSegNet: Volumetric CNNs for Semantic Part Segmentation of 3D Shapes)</news:title>
   <news:publication_date>2026-06-08T20:37:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698506</loc>
  <lastmod>2026-06-08T20:36:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>定義モデルによる答えの発見（Finding the Answers With Definition Models）</news:title>
   <news:publication_date>2026-06-08T20:36:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698504</loc>
  <lastmod>2026-06-08T20:36:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多言語情報抽出パイプラインによる調査報道支援（A Multilingual Information Extraction Pipeline for Investigative Journalism）</news:title>
   <news:publication_date>2026-06-08T20:36:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698502</loc>
  <lastmod>2026-06-08T20:36:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層線形モデルによる授業規模と学習成果の関係検証（Hierarchical Linear Modeling Approach to Measuring the Effects of Class Size and Other Classroom Characteristics on Student Learning in an Active-Learning Based Introductory Physics Course）</news:title>
   <news:publication_date>2026-06-08T20:36:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698500</loc>
  <lastmod>2026-06-08T19:45:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>競走馬の虹彩と眼周囲を使った個体識別（Iris and Periocular Recognition in Arabian Race Horses Using Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-08T19:45:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698498</loc>
  <lastmod>2026-06-08T19:44:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュース翻訳タスクへのMicrosoftの提出（Microsoft’s Submission to the WMT2018 News Translation Task）</news:title>
   <news:publication_date>2026-06-08T19:44:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698496</loc>
  <lastmod>2026-06-08T19:44:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データドロップアウト：畳み込みニューラルネットワークの訓練データ最適化（Data Dropout: Optimizing Training Data for Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-08T19:44:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698494</loc>
  <lastmod>2026-06-08T19:44:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件カーネル平均埋め込みのハイパーパラメータ学習（Hyperparameter Learning for Conditional Kernel Mean Embeddings with Rademacher Complexity Bounds）</news:title>
   <news:publication_date>2026-06-08T19:44:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698492</loc>
  <lastmod>2026-06-08T19:44:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲートテレポーテーションに基づく普遍的盲目量子計算（Gate Teleportation-based Universal Blind Quantum Computation）</news:title>
   <news:publication_date>2026-06-08T19:44:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698490</loc>
  <lastmod>2026-06-08T19:44:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オープンデータを使った人間開発指数（HDI）の政策最適化モデル（Open Data Analytical Model for Human Development Index Optimization to Support Government Policy）</news:title>
   <news:publication_date>2026-06-08T19:44:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698488</loc>
  <lastmod>2026-06-08T19:43:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ上の半教師あり学習にGANを応用する（Semi-supervised Learning on Graphs with Generative Adversarial Nets）</news:title>
   <news:publication_date>2026-06-08T19:43:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698486</loc>
  <lastmod>2026-06-08T18:52:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>将来実験に向けたパートン分布の理論的展望 (Theoretical perspective for the future experiments on parton densities)</news:title>
   <news:publication_date>2026-06-08T18:52:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698484</loc>
  <lastmod>2026-06-08T18:52:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>友人を介した小さな漏洩がもたらすリスク（What’s a Little Leakage Between Friends?）</news:title>
   <news:publication_date>2026-06-08T18:52:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698482</loc>
  <lastmod>2026-06-08T18:52:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群衆流の注目機構と予測（Attentive Crowd Flow Machines）</news:title>
   <news:publication_date>2026-06-08T18:52:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698480</loc>
  <lastmod>2026-06-08T18:51:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観測量間の動的構造を抽出するためのベクトル値再生核ヒルベルト空間における動的モード分解（Dynamic mode decomposition in vector-valued reproducing kernel Hilbert spaces for extracting dynamical structure among observables）</news:title>
   <news:publication_date>2026-06-08T18:51:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698478</loc>
  <lastmod>2026-06-08T18:51:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Extractive Adversarial Networksによる高再現率な説明手法（Extractive Adversarial Networks: High-Recall Explanations for Identifying Personal Attacks in Social Media Posts）</news:title>
   <news:publication_date>2026-06-08T18:51:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698476</loc>
  <lastmod>2026-06-08T18:51:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低精度・スパースニューラルネットワークの学習と学習可能な正則化（Learning Sparse Low-Precision Neural Networks With Learnable Regularization）</news:title>
   <news:publication_date>2026-06-08T18:51:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698474</loc>
  <lastmod>2026-06-08T18:50:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボットの動作に“様式”を与えるコスト関数（Cost Functions for Robot Motion Style）</news:title>
   <news:publication_date>2026-06-08T18:50:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698472</loc>
  <lastmod>2026-06-08T17:59:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タグベース推薦システムをプロファイル注入攻撃から守る比較研究（Securing Tag-based recommender systems against profile injection attacks: A comparative study）</news:title>
   <news:publication_date>2026-06-08T17:59:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698470</loc>
  <lastmod>2026-06-08T17:58:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>配分問題における学習のための公正なアルゴリズム（Fair Algorithms for Learning in Allocation Problems）</news:title>
   <news:publication_date>2026-06-08T17:58:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698468</loc>
  <lastmod>2026-06-08T17:57:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Total Recall: 深層階層畳み込みネットワークによる交通標識認識（Total Recall: Understanding Traffic Signs using Deep Hierarchical Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-08T17:57:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698466</loc>
  <lastmod>2026-06-08T17:57:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語指示で操るスケッチ彩色システム（LUCSS: Language-based User-customized Colorization of Scene Sketches）</news:title>
   <news:publication_date>2026-06-08T17:57:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698464</loc>
  <lastmod>2026-06-08T17:57:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協調フィルタリングのためのオートエンコーダ大規模学習への試み（Towards Large Scale Training Of Autoencoders For Collaborative Filtering）</news:title>
   <news:publication_date>2026-06-08T17:57:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698462</loc>
  <lastmod>2026-06-08T17:57:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的データに対する自己注意ネットワークと請求処理への応用（A Self-Attention Network for Hierarchical Data Structures with an Application to Claims Management）</news:title>
   <news:publication_date>2026-06-08T17:57:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698460</loc>
  <lastmod>2026-06-08T17:56:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元ガウス型グラフモデルにおける一様推論（UNIFORM INFERENCE IN HIGH-DIMENSIONAL GAUSSIAN GRAPHICAL MODELS）</news:title>
   <news:publication_date>2026-06-08T17:56:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698458</loc>
  <lastmod>2026-06-08T17:05:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WFIRSTの弱い重力レンズ計測における光度法赤方偏移校正要件（PHOTOMETRIC REDSHIFT CALIBRATION REQUIREMENTS FOR WFIRST WEAK LENSING COSMOLOGY: PREDICTIONS FROM CANDELS）</news:title>
   <news:publication_date>2026-06-08T17:05:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698456</loc>
  <lastmod>2026-06-08T16:58:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトル協調フィルタリング（Spectral Collaborative Filtering）</news:title>
   <news:publication_date>2026-06-08T16:58:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698454</loc>
  <lastmod>2026-06-08T16:57:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SDSS銀河のHIガスと質量-金属量関係（HI gas content of SDSS galaxies revealed by ALFALFA: implications for the mass-metallicity relation and the environmental dependence of HI in the local Universe）</news:title>
   <news:publication_date>2026-06-08T16:57:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698452</loc>
  <lastmod>2026-06-08T16:56:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機能的サイドチャネルのデータ駆動デバッグ（Data-Driven Debugging for Functional Side Channels）</news:title>
   <news:publication_date>2026-06-08T16:56:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698450</loc>
  <lastmod>2026-06-08T16:56:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペルセウス銀河団コアの密度揺らぎはスロッシングかAGNか（What fraction of the density fluctuations in the Perseus cluster core is due to gas sloshing rather than AGN feedback?）</news:title>
   <news:publication_date>2026-06-08T16:56:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698448</loc>
  <lastmod>2026-06-08T16:55:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M31の北部円盤におけるChandraとHubbleの比較（COMPARING CHANDRA AND HUBBLE IN THE NORTHERN DISK OF M31）</news:title>
   <news:publication_date>2026-06-08T16:55:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698446</loc>
  <lastmod>2026-06-08T16:55:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で量子カオスの“見分け”をする（Machine learning, quantum chaos, and pseudorandom evolution）</news:title>
   <news:publication_date>2026-06-08T16:55:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698444</loc>
  <lastmod>2026-06-08T16:03:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガイド付き補助監督によるエンドツーエンド自動運転学習（Learning End-to-end Autonomous Driving using Guided Auxiliary Supervision）</news:title>
   <news:publication_date>2026-06-08T16:03:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698442</loc>
  <lastmod>2026-06-08T15:56:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネスト化したマルチインスタンス画像分類（Nested Multi-Instance Image Classification）</news:title>
   <news:publication_date>2026-06-08T15:56:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698440</loc>
  <lastmod>2026-06-08T15:55:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンス中心注意ネットワークによる人と物の関係検出（iCAN: Instance-Centric Attention Network for Human-Object Interaction Detection）</news:title>
   <news:publication_date>2026-06-08T15:55:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698438</loc>
  <lastmod>2026-06-08T15:55:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学際的視点で「現実世界」を再定義する教育研究（Using disciplinary perspectives to refine conceptions of the &amp;quot;real world&amp;quot;）</news:title>
   <news:publication_date>2026-06-08T15:55:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698436</loc>
  <lastmod>2026-06-08T15:54:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非侵襲的な転倒検出へ向けた時空間畳み込みオートエンコーダの応用（DeepFall – Non-invasive Fall Detection with Deep Spatio-Temporal Convolutional Autoencoders）</news:title>
   <news:publication_date>2026-06-08T15:54:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698434</loc>
  <lastmod>2026-06-08T15:53:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的モーメンタム手法の統一的解析（A Unified Analysis of Stochastic Momentum Methods for Deep Learning）</news:title>
   <news:publication_date>2026-06-08T15:53:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698432</loc>
  <lastmod>2026-06-08T15:53:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類データセットの特徴付け — メタラーニングのためのメタフィーチャ研究（Characterizing classification datasets: a study of meta-features for meta-learning）</news:title>
   <news:publication_date>2026-06-08T15:53:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698430</loc>
  <lastmod>2026-06-08T15:01:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列脳機能接続を深層学習する（Deep Chronnectome Learning via Full Bidirectional LSTM Networks for MCI Diagnosis）</news:title>
   <news:publication_date>2026-06-08T15:01:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698428</loc>
  <lastmod>2026-06-08T15:00:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LUDBによる12誘導心電図（ECG）波形境界注釈データベースの価値（LUDB: a new open-access validation tool for electrocardiogram delineation algorithms）</news:title>
   <news:publication_date>2026-06-08T15:00:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698426</loc>
  <lastmod>2026-06-08T15:00:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>robot gym: クラウド上のシミュレーションで加速するロボット学習（robot gym: accelerated robot training through simulation in the cloud with ROS and Gazebo）</news:title>
   <news:publication_date>2026-06-08T15:00:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698424</loc>
  <lastmod>2026-06-08T15:00:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-08T15:00:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698422</loc>
  <lastmod>2026-06-08T15:00:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-08T15:00:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
</urlset>
