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   <news:title>音声から「屋外録音」時の3D顔動作を合成する技術（Synthesising 3D Facial Motion from “In-the-Wild” Speech）</news:title>
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   <news:title>大量のツイートに基づく市民の特徴付け（Characterization of citizens using word2vec and latent topic analysis in a large set of tweets）</news:title>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>オミクスデータの統合的コンセンサスクラスタリングのための多重カーネル学習（Multiple kernel learning for integrative consensus clustering of ’omic datasets）</news:title>
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   <news:title>生成モデルの精度と網羅性を分離して評価する手法の改良（Improved Precision and Recall Metric for Assessing Generative Models）</news:title>
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    <news:language>ja</news:language>
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   <news:title>SR-GANによるゼロショット学習の改良（SR-GAN: SEMANTIC RECTIFYING GENERATIVE ADVERSARIAL NETWORK FOR ZERO-SHOT LEARNING）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>継続学習の三つのシナリオ（Three scenarios for continual learning）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ニューラルネットワークにおける深さの分離：実際に何が分離されているのか？ (Depth Separations in Neural Networks: What is Actually Being Separated?)</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>強化学習アルゴリズム間の統計比較入門（A Hitchhiker’s Guide to Statistical Comparisons of Reinforcement Learning Algorithms）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>配列情報から作る機能連携ネットワークによる疾患遺伝子の優先順位付け（Disease gene prioritization using network topological analysis from a sequence based human functional linkage network）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>電力品質イベントの効率的特徴選択：2次元粒子群法によるアプローチ (Efficient Feature Selection of Power Quality Events using Two Dimensional (2D) Particle Swarms)</news:title>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>医用画像に対する敵対的攻撃の制御パラメータとデータセット規模の影響（Influence of Control Parameters and the Size of Biomedical Image Datasets on the Success of Adversarial Attacks）</news:title>
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    <news:language>ja</news:language>
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   <news:title>前処理で拡張する病理画像解析の実務的意義（Segmenting Potentially Cancerous Areas in Prostate Biopsies）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ニューラルネットワークの過剰パラメータ化が勾配混乱と確率的勾配降下に与える影響 (The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent)</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/729308</loc>
  <lastmod>2026-08-31T14:33:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>結合辞書学習による高速な特徴空間同定（A Fast Dictionary Learning Method for Coupled Feature Space Learning）</news:title>
   <news:publication_date>2026-08-31T14:33:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/729306</loc>
  <lastmod>2026-08-31T13:41:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>識別子埋め込みによるソースコードの意味表現（Semantic Source Code Models Using Identifier Embeddings）</news:title>
   <news:publication_date>2026-08-31T13:41:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>差分進化法によるハイパーパラメータ探索の実用性評価（On the Performance of Differential Evolution for Hyperparameter Tuning）</news:title>
   <news:publication_date>2026-08-31T13:33:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/729302</loc>
  <lastmod>2026-08-31T13:33:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>大視点差下での全画面記述子学習が示す実務インパクト（Learning Whole-Image Descriptors for Real-time Loop Detection and Kidnap Recovery under Large Viewpoint Difference）</news:title>
   <news:publication_date>2026-08-31T13:33:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/729300</loc>
  <lastmod>2026-08-31T13:33:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lean Residual Networks（LeanResNet: A Low-cost Yet Effective Convolutional Residual Networks）</news:title>
   <news:publication_date>2026-08-31T13:33:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/729298</loc>
  <lastmod>2026-08-31T13:31:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像クラスタリングのための深層包括的相関マイニング（Deep Comprehensive Correlation Mining for Image Clustering）</news:title>
   <news:publication_date>2026-08-31T13:31:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/729296</loc>
  <lastmod>2026-08-31T13:31:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>視覚とオドメトリのみで到達する学習型屋内自律航行（Deep Reinforcement Learning for Mapless Indoor Navigation）</news:title>
   <news:publication_date>2026-08-31T13:31:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/729294</loc>
  <lastmod>2026-08-31T13:30:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト予測におけるトピックモデルの統計的枠組み（A framework for streamlined statistical prediction using topic models）</news:title>
   <news:publication_date>2026-08-31T13:30:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/729291</loc>
  <lastmod>2026-08-31T12:38:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GraphTSNE（GRAPHTSNE: A VISUALIZATION TECHNIQUE FOR GRAPH-STRUCTURED DATA）</news:title>
   <news:publication_date>2026-08-31T12:38:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/729289</loc>
  <lastmod>2026-08-31T12:37:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変形可能カーネルを学習して画像・動画のノイズ除去を改善する手法（Learning Deformable Kernels for Image and Video Denoising）</news:title>
   <news:publication_date>2026-08-31T12:37:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/729287</loc>
  <lastmod>2026-08-31T12:37:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙的ペアによる非対応画像変換の強化（Implicit Pairs for Boosting Unpaired Image-to-Image Translation）</news:title>
   <news:publication_date>2026-08-31T12:37:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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  <loc>https://aibr.jp/archives/729285</loc>
  <lastmod>2026-08-31T12:36:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層メタ学習とMPPIによる誘導法の学習（Learning to Guide: Guidance Law Based on Deep Meta-learning and Model Predictive Path Integral Control）</news:title>
   <news:publication_date>2026-08-31T12:36:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/729283</loc>
  <lastmod>2026-08-31T12:36:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>イベントログ属性を活用したRNNベースの予測（Exploiting Event Log Event Attributes in RNN Based Prediction）</news:title>
   <news:publication_date>2026-08-31T12:36:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/729281</loc>
  <lastmod>2026-08-31T12:36:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DuBox: アンカーボックス不要の物体検出（DuBox: No-Prior Box Objection Detection via Residual Dual Scale Detectors）</news:title>
   <news:publication_date>2026-08-31T12:36:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/729279</loc>
  <lastmod>2026-08-31T12:35:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オプションを分離するヘリンガー距離正則化（Disentangling Options with Hellinger Distance Regularizer）</news:title>
   <news:publication_date>2026-08-31T12:35:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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  <loc>https://aibr.jp/archives/729277</loc>
  <lastmod>2026-08-31T11:44:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話型強化学習における「良い教師」とは何か（Improving interactive reinforcement learning: What makes a good teacher?）</news:title>
   <news:publication_date>2026-08-31T11:44:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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  <loc>https://aibr.jp/archives/729275</loc>
  <lastmod>2026-08-31T11:43:56Z</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歌声合成（Singing voice synthesis based on convolutional neural networks）</news:title>
   <news:publication_date>2026-08-31T11:43:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/729273</loc>
  <lastmod>2026-08-31T11:43:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平面領域における共形不変量の境界挙動（BOUNDARY BEHAVIOUR OF SOME CONFORMAL INVARIANTS ON PLANAR DOMAINS）</news:title>
   <news:publication_date>2026-08-31T11:43:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/729271</loc>
  <lastmod>2026-08-31T11:42:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テレビCMの単純接触効果が購買行動に与える影響の機械学習的測定（Measuring the influence of mere exposure effect of TV commercial adverts on purchase behavior based on machine learning prediction models）</news:title>
   <news:publication_date>2026-08-31T11:42:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/729269</loc>
  <lastmod>2026-08-31T11:42:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルネットワークにおける個人化嗜好学習を用いたキャッシュ戦略（A Personalized Preference Learning Framework for Caching in Mobile Networks）</news:title>
   <news:publication_date>2026-08-31T11:42:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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  <lastmod>2026-08-31T11:42:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己批判的n-step学習による画像キャプショニングの改善（Self-critical n-step Training for Image Captioning）</news:title>
   <news:publication_date>2026-08-31T11:42:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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  <lastmod>2026-08-31T11:42:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の意思決定を予測する ― 行動理論と機械学習の融合（Predicting human decisions with behavioral theories and machine learning）</news:title>
   <news:publication_date>2026-08-31T11:42:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/729263</loc>
  <lastmod>2026-08-31T10:50:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>熱画像におけるサリエンシーマップを用いた歩行者検出（Pedestrian Detection in Thermal Images using Saliency Maps）</news:title>
   <news:publication_date>2026-08-31T10:50:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729261</loc>
  <lastmod>2026-08-31T10:40:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層六方晶窒化ホウ素における量子放出体の原子スケール位置特定（Atomic Localization of Quantum Emitters in Multilayer Hexagonal Boron Nitride）</news:title>
   <news:publication_date>2026-08-31T10:40:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729259</loc>
  <lastmod>2026-08-31T10:39:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グローバル共分散プーリングが変える表現学習（Deep CNNs Meet Global Covariance Pooling: Better Representation and Generalization）</news:title>
   <news:publication_date>2026-08-31T10:39:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729257</loc>
  <lastmod>2026-08-31T10:39:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然のサーフゾーンにおける破砕波の割合（The Fraction of Broken Waves in Natural Surf Zones）</news:title>
   <news:publication_date>2026-08-31T10:39:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729255</loc>
  <lastmod>2026-08-31T10:38:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰系列モデルにおける大域正規化と局所正規化の実証的比較：連続緩和によるビームサーチ適用 (An Empirical Investigation of Global and Local Normalization for Recurrent Neural Sequence Models Using a Continuous Relaxation to Beam Search)</news:title>
   <news:publication_date>2026-08-31T10:38:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729253</loc>
  <lastmod>2026-08-31T10:38:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>日常シーンの跳ね返りを学ぶ（Bounce and Learn: Modeling Scene Dynamics with Real-World Bounces）</news:title>
   <news:publication_date>2026-08-31T10:38:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729251</loc>
  <lastmod>2026-08-31T10:38:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ライドソーシングサービスの時空間特徴学習（Learning Spatiotemporal Features of Ride-sourcing Services with Fusion Convolutional Network）</news:title>
   <news:publication_date>2026-08-31T10:38:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729249</loc>
  <lastmod>2026-08-31T09:46:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公理に基づくニューラルランキングモデルの正則化（An Axiomatic Approach to Regularizing Neural Ranking Models）</news:title>
   <news:publication_date>2026-08-31T09:46:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729247</loc>
  <lastmod>2026-08-31T09:36:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチチャンネル注意選択GANによる視点間画像変換の進展（Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation）</news:title>
   <news:publication_date>2026-08-31T09:36:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729245</loc>
  <lastmod>2026-08-31T09:36:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個人化リランキングによる推薦精度の向上（Personalized Re-ranking for Recommendation）</news:title>
   <news:publication_date>2026-08-31T09:36:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729243</loc>
  <lastmod>2026-08-31T09:35:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Tracking Machine LearningチャレンジのAccuracyフェーズ（The Tracking Machine Learning challenge: Accuracy phase）</news:title>
   <news:publication_date>2026-08-31T09:35:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729241</loc>
  <lastmod>2026-08-31T09:35:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小窓に基づくコンパクトなエピソードの発見（Discovering Episodes with Compact Minimal Windows）</news:title>
   <news:publication_date>2026-08-31T09:35:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729239</loc>
  <lastmod>2026-08-31T09:34:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多枝分岐テンソルネットワークによる判別分析の効率化（Multi-Branch Tensor Network Structure for Tensor-Train Discriminant Analysis）</news:title>
   <news:publication_date>2026-08-31T09:34:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729237</loc>
  <lastmod>2026-08-31T09:34:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>好奇心駆動iLQR：モデル不確実性を解消するMBRL（Curious iLQR: Resolving Uncertainty in Model-based RL）</news:title>
   <news:publication_date>2026-08-31T09:34:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729235</loc>
  <lastmod>2026-08-31T08:42:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話型システムとの関わりを学習する：公開博物館における深層強化学習のフィールドスタディ (Learning to Engage with Interactive Systems: A Field Study on Deep Reinforcement Learning in a Public Museum)</news:title>
   <news:publication_date>2026-08-31T08:42:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729233</loc>
  <lastmod>2026-08-31T08:42:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CMIP5に基づく全球平均地上気温予測の信頼性向上（Improved reliability and accuracy of CMIP5 global mean surface temperature projections）</news:title>
   <news:publication_date>2026-08-31T08:42:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729231</loc>
  <lastmod>2026-08-31T08:41:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関節空間とデカルト空間におけるポリシー探索の比較（A Comparison of Policy Search in Joint Space and Cartesian Space for Refinement of Skills）</news:title>
   <news:publication_date>2026-08-31T08:41:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729229</loc>
  <lastmod>2026-08-31T08:40:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミリ波大規模MIMOシステムの深層CNNによるチャネル推定（Deep CNN-Based Channel Estimation for mmWave Massive MIMO Systems）</news:title>
   <news:publication_date>2026-08-31T08:40:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729227</loc>
  <lastmod>2026-08-31T08:40:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的カーネルSVMによる不確かさを考慮した分類（Probabilistic Kernel Support Vector Machines）</news:title>
   <news:publication_date>2026-08-31T08:40:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729225</loc>
  <lastmod>2026-08-31T08:40:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光り輝く星雲の化学組成が示す謎（Latest advances in the abundance discrepancy problem in photoionized nebulae）</news:title>
   <news:publication_date>2026-08-31T08:40:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729223</loc>
  <lastmod>2026-08-31T08:40:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超巨大質量ミリ秒パルサーの相対論的シャピロ遅延測定（Relativistic Shapiro delay measurements of an extremely massive millisecond pulsar）</news:title>
   <news:publication_date>2026-08-31T08:40:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729221</loc>
  <lastmod>2026-08-31T07:48:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実務に結びつけるプログラミング言語教育の再設計（From Theory to Systems: A Grounded Approach to Programming Language Education）</news:title>
   <news:publication_date>2026-08-31T07:48:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729219</loc>
  <lastmod>2026-08-31T07:48:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在k単体（latent k‑simplex）の発見：Subset Smoothingによる準入力疎性アルゴリズム (Finding a latent k−simplex in O∗(k · nnz(data)) time via Subset Smoothing)</news:title>
   <news:publication_date>2026-08-31T07:48:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729217</loc>
  <lastmod>2026-08-31T07:48:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メモリ駆動型強化学習の概観（A Short Survey on Memory Based Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-31T07:48:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729215</loc>
  <lastmod>2026-08-31T07:47:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>希少語がもたらす問題と修正法（Rare Words: A Major Problem for Contextualized Embeddings and How to Fix it by Attentive Mimicking）</news:title>
   <news:publication_date>2026-08-31T07:47:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729213</loc>
  <lastmod>2026-08-31T07:47:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SpeechYOLOによる音声オブジェクトの検出と局所化 (SpeechYOLO: Detection and Localization of Speech Objects)</news:title>
   <news:publication_date>2026-08-31T07:47:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729211</loc>
  <lastmod>2026-08-31T07:46:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビームプロファイラー・ネットワーク（Beam Profiler Network (BPNet) - A Deep Learning Approach to Mode Demultiplexing of Laguerre-Gaussian Optical Beams）</news:title>
   <news:publication_date>2026-08-31T07:46:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729209</loc>
  <lastmod>2026-08-31T07:46:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画からの対象物除去を時空間的に整合させるVORNet（VORNet: Spatio-temporally Consistent Video Inpainting for Object Removal）</news:title>
   <news:publication_date>2026-08-31T07:46:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729207</loc>
  <lastmod>2026-08-31T06:54:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈を考慮したアイテム表現の事前学習で買い物カゴ予測を変える（Pre-training of Context-aware Item Representation for Next Basket Recommendation）</news:title>
   <news:publication_date>2026-08-31T06:54:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729205</loc>
  <lastmod>2026-08-31T06:53:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一視点からの不確かさを扱う3D形状生成と多視点合成（Conditional Single-view Shape Generation for Multi-view Stereo Reconstruction）</news:title>
   <news:publication_date>2026-08-31T06:53:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729203</loc>
  <lastmod>2026-08-31T06:53:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dot-to-Dot: 説明可能な階層型強化学習によるロボット操作（Dot-to-Dot: Explainable Hierarchical Reinforcement Learning for Robotic Manipulation）</news:title>
   <news:publication_date>2026-08-31T06:53:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729201</loc>
  <lastmod>2026-08-31T06:52:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>代表性と情報価値を探る能動学習（Exploring Representativeness and Informativeness for Active Learning）</news:title>
   <news:publication_date>2026-08-31T06:52:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729199</loc>
  <lastmod>2026-08-31T06:52:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>月面画像の欠損復元を実現するU-Netによる深層ニューラルネットワーク（LUNAR SURFACE IMAGE RESTORATION USING U-NET BASED DEEP NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-08-31T06:52:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729197</loc>
  <lastmod>2026-08-31T06:52:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチラベル能動学習における最大コレントロピー基準を用いたロバストラベリング（Robust and Discriminative Labeling for Multi-label Active Learning Based on Maximum Correntropy Criterion）</news:title>
   <news:publication_date>2026-08-31T06:52:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729195</loc>
  <lastmod>2026-08-31T06:52:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BERT4Rec: シーケンシャル推薦における双方向トランスフォーマ表現（BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer）</news:title>
   <news:publication_date>2026-08-31T06:52:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729193</loc>
  <lastmod>2026-08-31T05:59:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース高分解能ハイパースペクトル画像における自動ターゲット検出（Automatic Target Detection for Sparse Hyperspectral Images）</news:title>
   <news:publication_date>2026-08-31T05:59:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729191</loc>
  <lastmod>2026-08-31T05:59:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重要特徴を選り分ける顔表情認識ネットワーク（EXPERTNet: Exigent Features Preservative Network for Facial Expression Recognition）</news:title>
   <news:publication_date>2026-08-31T05:59:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729189</loc>
  <lastmod>2026-08-31T05:58:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュースから医療へ：分野横断的談話分割の課題と展望（From News to Medical: Cross-domain Discourse Segmentation）</news:title>
   <news:publication_date>2026-08-31T05:58:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729187</loc>
  <lastmod>2026-08-31T05:58:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波形変換とモチーフベースのグラフ畳み込みリカレントニューラルネットを統合したハイブリッド交通速度予測手法 (A Hybrid Traffic Speed Forecasting Approach Integrating Wavelet Transform and Motif-based Graph Convolutional Recurrent Neural Network)</news:title>
   <news:publication_date>2026-08-31T05:58:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729185</loc>
  <lastmod>2026-08-31T05:57:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートラップトップバッグによる行動認識と緊急通知（SMART LAPTOP BAG WITH MACHINE LEARNING FOR ACTIVITY RECOGNITION）</news:title>
   <news:publication_date>2026-08-31T05:57:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729183</loc>
  <lastmod>2026-08-31T05:57:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像における異常の無監督合成（Unsupervised Synthesis of Anomalies in Videos: Transforming the Normal）</news:title>
   <news:publication_date>2026-08-31T05:57:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729181</loc>
  <lastmod>2026-08-31T05:06:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正則化コックスモデルにおける過学習の解析（Analysis of overfitting in the regularized Cox model）</news:title>
   <news:publication_date>2026-08-31T05:06:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729179</loc>
  <lastmod>2026-08-31T05:06:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ類似度損失と一般的ペア重み付け（Multi-Similarity Loss with General Pair Weighting for Deep Metric Learning）</news:title>
   <news:publication_date>2026-08-31T05:06:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729177</loc>
  <lastmod>2026-08-31T05:06:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度画像翻訳のための段階的GAN学習（Biphasic Learning of GANs for High-Resolution Image-to-Image Translation）</news:title>
   <news:publication_date>2026-08-31T05:06:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729175</loc>
  <lastmod>2026-08-31T05:04:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>D2D通信における分散スペクトラム割当てのためのマルチエージェント深層強化学習フレームワーク（A Multi-Agent Deep Reinforcement Learning based Spectrum Allocation Framework for D2D Communications）</news:title>
   <news:publication_date>2026-08-31T05:04:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729173</loc>
  <lastmod>2026-08-31T05:04:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>閉じた厳密エピソードの発見手法（Mining Closed Strict Episodes）</news:title>
   <news:publication_date>2026-08-31T05:04:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729171</loc>
  <lastmod>2026-08-31T05:04:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UR-FUNNY：マルチモーダル言語データセットによるユーモア理解（UR-FUNNY: A Multimodal Language Dataset for Understanding Humor）</news:title>
   <news:publication_date>2026-08-31T05:04:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729169</loc>
  <lastmod>2026-08-31T05:04:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Shakeoutによるニューラルネットワークの正則化と圧縮（Shakeout: A New Approach to Regularized Deep Neural Network Training）</news:title>
   <news:publication_date>2026-08-31T05:04:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729167</loc>
  <lastmod>2026-08-31T04:12:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声駆動インターフェースのリプレイ攻撃と対策（Towards Vulnerability Analysis of Voice-Driven Interfaces and Countermeasures for Replay Attacks）</news:title>
   <news:publication_date>2026-08-31T04:12:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729165</loc>
  <lastmod>2026-08-31T04:12:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし歌声変換の可能性（Unsupervised Singing Voice Conversion）</news:title>
   <news:publication_date>2026-08-31T04:12:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729163</loc>
  <lastmod>2026-08-31T04:11:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械文字起こしから人手文字起こしへの変換を学習するGAN（M2H-GAN: A GAN-based Mapping from Machine to Human Transcripts for Speech Understanding）</news:title>
   <news:publication_date>2026-08-31T04:11:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729161</loc>
  <lastmod>2026-08-31T04:11:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レンジ画像からのスーパークアドリック復元をCNNで高速化する試み（Recovery of Superquadrics from Range Images using Deep Learning: A Preliminary Study）</news:title>
   <news:publication_date>2026-08-31T04:11:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729159</loc>
  <lastmod>2026-08-31T04:10:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シミュレータ拡張型インタラクションネットワーク（Combining Physical Simulators and Object-Based Networks for Control）</news:title>
   <news:publication_date>2026-08-31T04:10:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729157</loc>
  <lastmod>2026-08-31T04:10:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GA-Net: Guided Aggregation Net が切り開くステレオ再構成の効率化（GA-Net: Guided Aggregation Net for End-to-end Stereo Matching）</news:title>
   <news:publication_date>2026-08-31T04:10:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729155</loc>
  <lastmod>2026-08-31T04:10:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未ラベルデータと物理則の組み込みによるPDE解法の深化（Deep-learning PDEs with unlabeled data and hardwiring physics laws）</news:title>
   <news:publication_date>2026-08-31T04:10:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729153</loc>
  <lastmod>2026-08-31T03:19:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HAKE: 人間行動知識エンジン（HAKE: Human Activity Knowledge Engine）</news:title>
   <news:publication_date>2026-08-31T03:19:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729151</loc>
  <lastmod>2026-08-31T03:19:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外れ値に強い自己学習型確率的主成分分析（Self-Paced Probabilistic Principal Component Analysis for Data with Outliers）</news:title>
   <news:publication_date>2026-08-31T03:19:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729149</loc>
  <lastmod>2026-08-31T03:18:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Pólygammaデータ拡張によるMMNLの非共役問題解消（Pólygamma Data Augmentation to address Non-conjugacy in the Bayesian Estimation of Mixed Multinomial Logit Models）</news:title>
   <news:publication_date>2026-08-31T03:18:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729147</loc>
  <lastmod>2026-08-31T03:18:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意コストと退職（Costly Attention and Retirement）</news:title>
   <news:publication_date>2026-08-31T03:18:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729145</loc>
  <lastmod>2026-08-31T03:18:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短文トピックモデリングの技術・応用・性能調査（Short Text Topic Modeling Techniques, Applications, and Performance: A Survey）</news:title>
   <news:publication_date>2026-08-31T03:18:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729143</loc>
  <lastmod>2026-08-31T03:17:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タンパク質-リガンド結合部位検出を改善する3Dセグメンテーション（Improving detection of protein-ligand binding sites with 3D segmentation）</news:title>
   <news:publication_date>2026-08-31T03:17:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729141</loc>
  <lastmod>2026-08-31T03:17:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース大規模データ向け統合オートエンコーダフィルター（An Integrated Autoencoder-Based Filter for Sparse Big Data）</news:title>
   <news:publication_date>2026-08-31T03:17:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729139</loc>
  <lastmod>2026-08-31T02:25:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>dipIQによるブラインド画像品質評価（dipIQ: Blind Image Quality Assessment by Learning-to-Rank Discriminable Image Pairs）</news:title>
   <news:publication_date>2026-08-31T02:25:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729137</loc>
  <lastmod>2026-08-31T02:25:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低リソース言語のためのエンドツーエンド音声合成（End-to-end Text-to-speech for Low-resource Languages by Cross-Lingual Transfer Learning）</news:title>
   <news:publication_date>2026-08-31T02:25:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729135</loc>
  <lastmod>2026-08-31T02:23:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特権情報を用いたカーネル法ベースの一クラス分類（OCKELM+: Kernel Extreme Learning Machine based One-class Classification using Privileged Information）</news:title>
   <news:publication_date>2026-08-31T02:23:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729133</loc>
  <lastmod>2026-08-31T02:23:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己相似性の一貫性と特徴識別性によるドメイン適応の改善（Towards Self-similarity Consistency and Feature Discrimination for Unsupervised Domain Adaptation）</news:title>
   <news:publication_date>2026-08-31T02:23:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729131</loc>
  <lastmod>2026-08-31T02:23:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中心を可変にした最大コレントロピー基準（Maximum Correntropy Criterion with Variable Center）</news:title>
   <news:publication_date>2026-08-31T02:23:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729129</loc>
  <lastmod>2026-08-31T02:22:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ埋め込み多層カーネルリッジ回帰によるワンクラス分類（Graph-Embedded Multi-layer Kernel Ridge Regression for One-class Classification）</news:title>
   <news:publication_date>2026-08-31T02:22:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729127</loc>
  <lastmod>2026-08-31T02:22:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トピックグルーパ：凝集型クラスタリングによるトピックモデル（Topic Grouper: An Agglomerative Clustering Approach to Topic Modeling）</news:title>
   <news:publication_date>2026-08-31T02:22:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729125</loc>
  <lastmod>2026-08-31T01:30:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>法分野分類の比較研究（Legal Area Classification: A Comparative Study of Text Classifiers on Singapore Supreme Court Judgments）</news:title>
   <news:publication_date>2026-08-31T01:30:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729123</loc>
  <lastmod>2026-08-31T01:30:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Transformable Bottleneck Networks（Transformable Bottleneck Networks）</news:title>
   <news:publication_date>2026-08-31T01:30:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729121</loc>
  <lastmod>2026-08-31T01:29:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小型深層学習RF分類器のためのオートエンコーダ訓練（AutoEncoders for Training Compact Deep Learning RF Classiﬁers for Wireless Protocols）</news:title>
   <news:publication_date>2026-08-31T01:29:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729119</loc>
  <lastmod>2026-08-31T01:28:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジストリームからの動的ノード埋め込み（Dynamic Node Embeddings from Edge Streams）</news:title>
   <news:publication_date>2026-08-31T01:28:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729117</loc>
  <lastmod>2026-08-31T01:28:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>残存使用可能寿命推定における関数データ解析の応用（Remaining Useful Life Estimation Using Functional Data Analysis）</news:title>
   <news:publication_date>2026-08-31T01:28:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729115</loc>
  <lastmod>2026-08-31T01:28:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化暗黙関数による形状テンプレート学習（Learning Shape Templates with Structured Implicit Functions）</news:title>
   <news:publication_date>2026-08-31T01:28:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729113</loc>
  <lastmod>2026-08-31T01:27:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠隔軌道にある巨大惑星の質量関数と起源（ON THE MASS FUNCTION, MULTIPLICITY, AND ORIGINS OF WIDE-ORBIT GIANT PLANETS）</news:title>
   <news:publication_date>2026-08-31T01:27:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729111</loc>
  <lastmod>2026-08-31T00:36:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形不確実性システムのサンプルベース学習モデル予測制御（Sample-Based Learning Model Predictive Control for Linear Uncertain Systems）</news:title>
   <news:publication_date>2026-08-31T00:36:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729109</loc>
  <lastmod>2026-08-31T00:26:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>水中ロボットのためのリアルタイム物理モデルベース色補正（Real-time Model-based Image Color Correction for Underwater Robots）</news:title>
   <news:publication_date>2026-08-31T00:26:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729107</loc>
  <lastmod>2026-08-31T00:25:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜眼底画像から貧血を検出する（Detecting Anemia from Retinal Fundus Images）</news:title>
   <news:publication_date>2026-08-31T00:25:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729105</loc>
  <lastmod>2026-08-31T00:24:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マクロカノニカルモデルによるテクスチャ合成（Macrocanonical Models for Texture Synthesis）</news:title>
   <news:publication_date>2026-08-31T00:24:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729103</loc>
  <lastmod>2026-08-31T00:24:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層動的最適化による改良LEACHとコスト効率の高いDeep Belief Network（Multi-level Dynamic Optimization of Intelligent LEACH with Cost Effective Deep Belief Network）</news:title>
   <news:publication_date>2026-08-31T00:24:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729101</loc>
  <lastmod>2026-08-31T00:24:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報理論に基づく潜在変数モデルの下限（INFORMATION THEORETIC LOWER BOUNDS ON NEGATIVE LOG LIKELIHOOD）</news:title>
   <news:publication_date>2026-08-31T00:24:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729099</loc>
  <lastmod>2026-08-31T00:24:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジコンピューティングを用いたインテリジェント映像監視システムの分散深層学習モデル（Distributed Deep Learning Model for Intelligent Video Surveillance Systems with Edge Computing）</news:title>
   <news:publication_date>2026-08-31T00:24:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729097</loc>
  <lastmod>2026-08-30T23:33:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観測から学ぶ逆強化学習で不十分なデモを超える（Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations）</news:title>
   <news:publication_date>2026-08-30T23:33:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729095</loc>
  <lastmod>2026-08-30T23:33:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>冗長マニピュレータの運動学と動力学を解くためのリカレントニューラルネットワーク体モデルの構築（Setup of a Recurrent Neural Network as a Body Model for Solving Inverse and Forward Kinematics as well as Dynamics for a Redundant Manipulator）</news:title>
   <news:publication_date>2026-08-30T23:33:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729093</loc>
  <lastmod>2026-08-30T23:32:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>bfloat16を活用した高精度計算の合理化（Leveraging the bfloat16 Artificial Intelligence Datatype For Higher-Precision Computations）</news:title>
   <news:publication_date>2026-08-30T23:32:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729091</loc>
  <lastmod>2026-08-30T23:32:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークの信頼できる予測誤差（Reliable Prediction Errors for Deep Neural Networks Using Test-Time Dropout）</news:title>
   <news:publication_date>2026-08-30T23:32:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729089</loc>
  <lastmod>2026-08-30T23:32:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚の意味情報を操る「制約なし」敵対的例（UNRESTRICTED ADVERSARIAL EXAMPLES VIA SEMANTIC MANIPULATION）</news:title>
   <news:publication_date>2026-08-30T23:32:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729087</loc>
  <lastmod>2026-08-30T23:31:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク潜在テンソル因子分解による漸進的マルチドメイン学習（Incremental Multi-domain Learning with Network Latent Tensor Factorization）</news:title>
   <news:publication_date>2026-08-30T23:31:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729085</loc>
  <lastmod>2026-08-30T23:31:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AP損失によるワンステージ物体検出の精度向上（Towards Accurate One-Stage Object Detection with AP-Loss）</news:title>
   <news:publication_date>2026-08-30T23:31:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729083</loc>
  <lastmod>2026-08-30T22:40:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>広帯域スペクトルにおける狭帯域信号の賢い識別法（Intelligent Wide-band Spectrum Classifier）</news:title>
   <news:publication_date>2026-08-30T22:40:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729081</loc>
  <lastmod>2026-08-30T22:39:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>境界を保つ深層ノイズ除去法が変える多光子イメージング（Boundary-Preserved Deep Denoising of the Stochastic Resonance Enhanced Multiphoton Images）</news:title>
   <news:publication_date>2026-08-30T22:39:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729079</loc>
  <lastmod>2026-08-30T22:39:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数ショットの模倣学習を実現する論理プログラム方策（Few-Shot Bayesian Imitation Learning with Logical Program Policies）</news:title>
   <news:publication_date>2026-08-30T22:39:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729077</loc>
  <lastmod>2026-08-30T22:38:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データから最適な決定木を学習する方法（Learning Optimal Decision Trees from Large Datasets）</news:title>
   <news:publication_date>2026-08-30T22:38:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729075</loc>
  <lastmod>2026-08-30T22:38:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間グラフの深層表現学習が拓く予測力（Spatio-Temporal Deep Graph Infomax）</news:title>
   <news:publication_date>2026-08-30T22:38:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729073</loc>
  <lastmod>2026-08-30T22:38:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再び遊ぼう：Atari環境における深層強化学習エージェントの変動性（Let’s Play Again: Variability of Deep Reinforcement Learning Agents in Atari Environments）</news:title>
   <news:publication_date>2026-08-30T22:38:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729071</loc>
  <lastmod>2026-08-30T22:38:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散バンディット学習：通信効率とほぼ最適な後悔（Distributed Bandit Learning: Near-Optimal Regret with Efficient Communication）</news:title>
   <news:publication_date>2026-08-30T22:38:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729069</loc>
  <lastmod>2026-08-30T21:46:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>環境変化へ継続的に適応するセマンティックセグメンテーション（ACE: Adapting to Changing Environments for Semantic Segmentation）</news:title>
   <news:publication_date>2026-08-30T21:46:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729067</loc>
  <lastmod>2026-08-30T21:38:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lmserの再訪と畳み込み層への展開（Revisit Lmser and its further development based on convolutional layers）</news:title>
   <news:publication_date>2026-08-30T21:38:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729065</loc>
  <lastmod>2026-08-30T21:38:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統計的分類における敵対学習――攻撃に対する防御の包括的レビュー（Adversarial Learning in Statistical Classification: A Comprehensive Review of Defenses Against Attacks）</news:title>
   <news:publication_date>2026-08-30T21:38:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729063</loc>
  <lastmod>2026-08-30T21:38:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QFactory：古典指示で遠隔に秘密の量子ビットを作る仕組み（QFactory: classically-instructed remote secret qubits preparation）</news:title>
   <news:publication_date>2026-08-30T21:38:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729061</loc>
  <lastmod>2026-08-30T21:37:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外れ値に強いスパース線形モデル推定（Outlier-robust estimation of a sparse linear model using ℓ1-penalized Huber’s M-estimator）</news:title>
   <news:publication_date>2026-08-30T21:37:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729059</loc>
  <lastmod>2026-08-30T21:37:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分推論を用いた計算イメージング逆問題（Variational Inference for Computational Imaging Inverse Problems）</news:title>
   <news:publication_date>2026-08-30T21:37:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729057</loc>
  <lastmod>2026-08-30T21:36:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所結合型スパイキングニューラルネットワークによる教師なし特徴学習（Locally Connected Spiking Neural Networks for Unsupervised Feature Learning）</news:title>
   <news:publication_date>2026-08-30T21:36:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729055</loc>
  <lastmod>2026-08-30T20:45:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Policy Gradientと教師あり学習の類似性（Similarities between policy gradient methods (PGM) in reinforcement learning (RL) and supervised learning (SL)）</news:title>
   <news:publication_date>2026-08-30T20:45:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729053</loc>
  <lastmod>2026-08-30T20:45:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的環境下でのエッジ計算における予算限定マルチアームド・バンディット（Multi-Armed Bandit for Energy-Eﬃcient and Delay-Sensitive Edge Computing in Dynamic Networks with Uncertainty）</news:title>
   <news:publication_date>2026-08-30T20:45:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729051</loc>
  <lastmod>2026-08-30T20:44:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化された電力負荷予測モデル構築の実務的勝利（Automatic Model Building in GEFCom 2017）</news:title>
   <news:publication_date>2026-08-30T20:44:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/729049</loc>
  <lastmod>2026-08-30T20:43:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MAANetによる画像超解像の実務的意義（MAANet: Multi-view Aware Attention Networks for Image Super-Resolution）</news:title>
   <news:publication_date>2026-08-30T20:43:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729047</loc>
  <lastmod>2026-08-30T20:43:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AMS-SFEによる意味特徴拡張を用いたマニフォールド整合（AMS-SFE: TOWARDS AN ALIGNMENT OF MANIFOLD STRUCTURES VIA SEMANTIC FEATURE EXPANSION FOR ZERO-SHOT LEARNING）</news:title>
   <news:publication_date>2026-08-30T20:43:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729045</loc>
  <lastmod>2026-08-30T20:43:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープニューラルネットワークにおけるリプシッツ正則化の結合効果（The coupling effect of Lipschitz regularization in deep neural networks）</news:title>
   <news:publication_date>2026-08-30T20:43:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729043</loc>
  <lastmod>2026-08-30T20:43:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成ハイブリッド表現による行動予測とノーリグレット学習（Generative Hybrid Representations for Activity Forecasting with No-Regret Learning）</news:title>
   <news:publication_date>2026-08-30T20:43:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729041</loc>
  <lastmod>2026-08-30T19:52:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平面弾性膜を貫通する能動粒子の貫通理論（Theory of active particle penetration through a planar elastic membrane）</news:title>
   <news:publication_date>2026-08-30T19:52:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729039</loc>
  <lastmod>2026-08-30T19:51:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランク畳み込み深層ニューラルネットワークによるマルチタスク学習（Low-Rank Deep Convolutional Neural Network for Multi-Task Learning）</news:title>
   <news:publication_date>2026-08-30T19:51:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729037</loc>
  <lastmod>2026-08-30T19:50:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>楽器音の生成における敵対的自己符号化器と音楽的条件付け（Assisted Sound Sample Generation with Musical Conditioning in Adversarial Auto-Encoders）</news:title>
   <news:publication_date>2026-08-30T19:50:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729035</loc>
  <lastmod>2026-08-30T19:50:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習で重力レンズの質量モデルを高速推定する手法（The use of convolutional neural networks for modelling large optically-selected strong galaxy-lens samples）</news:title>
   <news:publication_date>2026-08-30T19:50:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729033</loc>
  <lastmod>2026-08-30T19:50:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OpenKIによるWeb規模知識抽出の革新（OpenKI: Integrating Open Information Extraction and Knowledge Bases with Relation Inference）</news:title>
   <news:publication_date>2026-08-30T19:50:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729031</loc>
  <lastmod>2026-08-30T19:50:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>膝の変形性関節症進行予測を変えるマルチモーダル学習（Multimodal Machine Learning-based Knee Osteoarthritis Progression Prediction from Plain Radiographs and Clinical Data）</news:title>
   <news:publication_date>2026-08-30T19:50:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729029</loc>
  <lastmod>2026-08-30T19:49:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>等化ダイナミクスと等量子数の影響（Equilibration dynamics and isospin effects in nuclear reactions）</news:title>
   <news:publication_date>2026-08-30T19:49:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729027</loc>
  <lastmod>2026-08-30T18:57:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>保険料率設計における木構造機械学習の実務的価値（Boosting insights in insurance tariffplans with tree-based machine learning methods）</news:title>
   <news:publication_date>2026-08-30T18:57:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729025</loc>
  <lastmod>2026-08-30T18:57:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位置認識畳み込みネットワークによる交通予測（Position-Aware Convolutional Networks for Traffic Prediction）</news:title>
   <news:publication_date>2026-08-30T18:57:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729023</loc>
  <lastmod>2026-08-30T18:57:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信用スコアリングにおける拒否推論のための深層生成モデル（Deep Generative Models for Reject Inference in Credit Scoring）</news:title>
   <news:publication_date>2026-08-30T18:57:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729021</loc>
  <lastmod>2026-08-30T18:56:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ナノワイヤ電界効果センサーのベイズ逆問題（Bayesian inversion for nanowire field-effect sensors）</news:title>
   <news:publication_date>2026-08-30T18:56:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729019</loc>
  <lastmod>2026-08-30T18:56:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DAEベースの歌声分離における写像関数の解明（EXAMINING THE MAPPING FUNCTIONS OF DENOISING AUTOENCODERS IN SINGING VOICE SEPARATION）</news:title>
   <news:publication_date>2026-08-30T18:56:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729017</loc>
  <lastmod>2026-08-30T18:56:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NEOCamによる外宇宙時間領域天文学の機会（Opportunities in Time-Domain Extragalactic Astrophysics with the NASA Near-Earth Object Camera (NEOCam))</news:title>
   <news:publication_date>2026-08-30T18:56:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729015</loc>
  <lastmod>2026-08-30T18:55:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SDC特徴の訓練法に関する実証的評価（An Empirical Evaluation Study on the Training of SDC Features for Dense Pixel Matching）</news:title>
   <news:publication_date>2026-08-30T18:55:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729013</loc>
  <lastmod>2026-08-30T18:04:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピクセル領域における幅ベース計画の深層方策（Deep Policies for Width-Based Planning in Pixel Domains）</news:title>
   <news:publication_date>2026-08-30T18:04:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729011</loc>
  <lastmod>2026-08-30T18:04:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>直接撮像による系外惑星発見の限界を押し上げる深層学習（Pushing the Limits of Exoplanet Discovery via Direct Imaging with Deep Learning）</news:title>
   <news:publication_date>2026-08-30T18:04:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729009</loc>
  <lastmod>2026-08-30T18:03:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幾何学考慮型最大尤度法による内在次元推定（Geometry-Aware Maximum Likelihood Estimation of Intrinsic Dimension）</news:title>
   <news:publication_date>2026-08-30T18:03:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729007</loc>
  <lastmod>2026-08-30T18:03:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>計測インフラからのストリーミング特徴ベース圧縮法（A streaming feature-based compression method for data from instrumented infrastructure）</news:title>
   <news:publication_date>2026-08-30T18:03:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729005</loc>
  <lastmod>2026-08-30T18:02:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>写真のような画像操作に向けた生成型オートエンコーダのバランス成長（Towards Photographic Image Manipulation with Balanced Growing of Generative Autoencoders）</news:title>
   <news:publication_date>2026-08-30T18:02:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729003</loc>
  <lastmod>2026-08-30T18:02:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>指先で触らず操作するインターフェース（AirPen: A Touchless Fingertip Based Gestural Interface for Smartphones and Head-Mounted Devices）</news:title>
   <news:publication_date>2026-08-30T18:02:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/729001</loc>
  <lastmod>2026-08-30T18:02:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トリミングと固有値比制約による頑健なモデルベース分類（A robust approach to model-based classification based on trimming and constraints）</news:title>
   <news:publication_date>2026-08-30T18:02:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728999</loc>
  <lastmod>2026-08-30T17:10:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PWOC-3Dによる3Dシーンフロー推定の効率化（PWOC-3D: Deep Occlusion-Aware End-to-End Scene Flow Estimation）</news:title>
   <news:publication_date>2026-08-30T17:10:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728997</loc>
  <lastmod>2026-08-30T17:10:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>能力とコンテキストに基づく適応システムの提案（Ability and Context Based Adaptive System: A Proposal for Machine Learning Approach）</news:title>
   <news:publication_date>2026-08-30T17:10:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728995</loc>
  <lastmod>2026-08-30T17:10:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔のデオクルージョン：3Dモーファブルモデルと生成的敵対ネットワークによる手法（Face De-occlusion using 3D Morphable Model and Generative Adversarial Network）</news:title>
   <news:publication_date>2026-08-30T17:10:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728993</loc>
  <lastmod>2026-08-30T17:09:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VOiCES遠距離チャレンジに向けたSTCの話者認識システム（STC Speaker Recognition Systems for the VOiCES From a Distance Challenge）</news:title>
   <news:publication_date>2026-08-30T17:09:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728991</loc>
  <lastmod>2026-08-30T17:09:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層単一画像超解像の敵対的攻撃に対する頑健性評価（Evaluating Robustness of Deep Image Super-Resolution Against Adversarial Attacks）</news:title>
   <news:publication_date>2026-08-30T17:09:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728989</loc>
  <lastmod>2026-08-30T17:09:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>断面画像から3D複合材料の熱伝導を予測する深層学習手法（Deep learning methods based on cross-section images for predicting effective thermal conductivity of composites）</news:title>
   <news:publication_date>2026-08-30T17:09:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728987</loc>
  <lastmod>2026-08-30T17:09:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルメディアにおけるテキスト正規化のためのSeq2Seq適応（Adapting Sequence to Sequence models for Text Normalization in Social Media）</news:title>
   <news:publication_date>2026-08-30T17:09:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728985</loc>
  <lastmod>2026-08-30T16:18:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エゴセン視線予測の深掘り（Digging Deeper into Egocentric Gaze Prediction）</news:title>
   <news:publication_date>2026-08-30T16:18:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728983</loc>
  <lastmod>2026-08-30T16:18:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフウェーブレットニューラルネットワーク（Graph Wavelet Neural Network）</news:title>
   <news:publication_date>2026-08-30T16:18:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728981</loc>
  <lastmod>2026-08-30T16:17:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分離表現学習に基づく教師なし音声ドメイン適応による堅牢な音声認識（Unsupervised Speech Domain Adaptation Based on Disentangled Representation Learning for Robust Speech Recognition）</news:title>
   <news:publication_date>2026-08-30T16:17:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728979</loc>
  <lastmod>2026-08-30T16:16:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種分類器の統合と蒸留による知識融合（Unifying Heterogeneous Classiﬁers with Distillation）</news:title>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>SDNにおけるスケジューリング関数設計を強化学習で最適化する手法（Effective Scheduling Function Design in SDN through Deep Reinforcement Learning）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>プライバシー保護のための分散レイヤ分割学習（Distributed Layer-Partitioned Training for Privacy-Preserved Deep Learning）</news:title>
   <news:publication_date>2026-08-30T16:16:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>超音波舌画像を用いた音声からの発話器予測（DNN-based Acoustic-to-Articulatory Inversion using Ultrasound Tongue Imaging）</news:title>
   <news:publication_date>2026-08-30T16:16:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>機械学習で位相図を読み解く──1次元拡張ハバード模型の事例研究（Machine Learning Phase Diagram in the Half-filled One-dimensional Extended Hubbard Model）</news:title>
   <news:publication_date>2026-08-30T15:23:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>言語と視覚モデルの表現ハブを評価する（Evaluating the Representational Hub of Language and Vision Models）</news:title>
   <news:publication_date>2026-08-30T15:14:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>直接音声間翻訳の実現（Direct speech-to-speech translation with a sequence-to-sequence model）</news:title>
   <news:publication_date>2026-08-30T15:14:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/728965</loc>
  <lastmod>2026-08-30T15:13:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層自己回帰密度推定器に基づく教師あり異常検知（Supervised Anomaly Detection based on Deep Autoregressive Density Estimators）</news:title>
   <news:publication_date>2026-08-30T15:13:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>評価時のバッチ正規化統計推定（EvalNorm: Estimating Batch Normalization Statistics for Evaluation）</news:title>
   <news:publication_date>2026-08-30T15:13:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/728961</loc>
  <lastmod>2026-08-30T15:13:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互作用を意識した適応戦略による合流場面での意思決定（Interaction-aware Decision Making with Adaptive Strategies under Merging Scenarios）</news:title>
   <news:publication_date>2026-08-30T15:13:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/728959</loc>
  <lastmod>2026-08-30T15:13:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>攻撃と防御を同時に学習するCycleAdvGANの提案（Cycle-Consistent Adversarial GAN: the integration of adversarial attack and defense）</news:title>
   <news:publication_date>2026-08-30T15:13:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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