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   <news:title>AttentionXMLによる極大多ラベルテキスト分類（AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification）</news:title>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>クラス非依存な物体の数え上げ（Class-Agnostic Counting）</news:title>
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   <news:title>符号付き決定過程の学習─主小行列割当問題を通して（Learning Signed Determinantal Point Processes through the Principal Minor Assignment Problem）</news:title>
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   <news:title>非ランダムに欠損する電子健康記録を解析する潜在トピックモデル（A latent topic model for mining heterogeneous non-randomly missing electronic health records data）</news:title>
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   <news:title>太陽コロナの性質と太陽風とのつながり (The Properties of the Solar Corona and Its Connection to the Solar Wind)</news:title>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>ジェームズ・ウェッブ望遠鏡で探る高赤方偏移超新星の検出と分類（DETECTION AND CLASSIFICATION OF SUPERNOVAE BEYOND Z ∼2 REDSHIFT WITH THE JAMES WEBB SPACE TELESCOPE）</news:title>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>参照信号を使わない音源分離評価法（REFERENCELESS PERFORMANCE EVALUATION OF AUDIO SOURCE SEPARATION USING DEEP NEURAL NETWORKS）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>RW Aur Aの色・偏光変動の解析（Analysis of colour and polarimetric variability of RW Aur A in 2010–2018）</news:title>
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    <news:language>ja</news:language>
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   <news:title>可換群作用の強外性とZ安定性の同値性（STRONGLY OUTER ACTIONS OF AMENABLE GROUPS ON Z-STABLE C*-ALGEBRAS）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>改良された共変性局所特徴検出の学習フレームワーク（An Improved Learning Framework for Covariant Local Feature Detection）</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>ガンマ線バーストから高速電波バーストへ（From gamma-ray bursts to fast radio bursts）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-30T08:54:59Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>顔写真から風刺画を自動生成する技術の要諦（CariGAN: Caricature Generation through Weakly Paired Adversarial Learning）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-30T08:04:12Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Query指向型抽出要約を無教師で両段階で学ぶ（Unsupervised Dual-Cascade Learning with Pseudo-Feedback Distillation for Query-based Extractive Summarization）</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>マルコフ決定過程における時間的正則化（Temporal Regularization in Markov Decision Process）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/706500</loc>
  <lastmod>2026-06-30T08:03:32Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Spark上で動く分散型ReliefFによる特徴選択（Distributed ReliefF based Feature Selection in Spark）</news:title>
   <news:publication_date>2026-06-30T08:03:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-30T08:02:46Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>真に教師なしの音声単語埋め込み――弱いトップダウン制約を用いたエンコーダ・デコーダモデルの提案（TRULY UNSUPERVISED ACOUSTIC WORD EMBEDDINGS USING WEAK TOP-DOWN CONSTRAINTS IN ENCODER-DECODER MODELS）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-30T08:02:32Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>HD 95086のデブリ円盤におけるCOガスの深掘り探索（Deep ALMA Search for CO Gas in the HD 95086 Debris Disc）</news:title>
   <news:publication_date>2026-06-30T08:02:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-30T08:02:18Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Dilated DenseNetsによる関係推論の効率化（Dilated DenseNets for Relational Reasoning）</news:title>
   <news:publication_date>2026-06-30T08:02:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-30T08:02:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>乗法的潜在力モデルの解説（Multiplicative Latent Force Models）</news:title>
   <news:publication_date>2026-06-30T08:02:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-30T07:11:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>助け合い：顧客間の提案抽出のための枠組み (Helping Each Other: A Framework for Customer-to-Customer Suggestion Mining)</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-30T07:02:57Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>過剰な不変性がもたらす敵対的脆弱性（Excessive Invariance Causes Adversarial Vulnerability）</news:title>
   <news:publication_date>2026-06-30T07:02:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-30T07:01:50Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>語順の不一致を埋める多言語ニューラル機械翻訳の工夫（Addressing Word-order Divergence in Multilingual Neural Machine Translation for extremely Low Resource Languages）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-30T07:01:27Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>マルチチャネル聴覚的アテンションを用いたエンドツーエンド音声キーワード検出（END-TO-END MODELS WITH AUDITORY ATTENTION IN MULTI-CHANNEL KEYWORD SPOTTING）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-30T07:01:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>電子ベースのイオン化プロファイルモニターによる横方向プロファイルの空間電荷歪みと補正法 (Space-charge distortion of transverse profiles measured by electron-based Ionization Profile Monitors and correction methods)</news:title>
   <news:publication_date>2026-06-30T07:01:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-30T07:00:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>多モーダル翻訳のための潜在変数モデル（Latent Variable Model for Multi-modal Translation）</news:title>
   <news:publication_date>2026-06-30T07:00:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/706478</loc>
  <lastmod>2026-06-30T07:00:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二つのGANを軸に知覚品質と歪みを両立する手法（Bi-GANs-ST for Perceptual Image Super-resolution）</news:title>
   <news:publication_date>2026-06-30T07:00:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/706476</loc>
  <lastmod>2026-06-30T06:08:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚品質と誤差のトレードオフを操る方法（Analyzing Perception-Distortion Tradeoff using Enhanced Perceptual Super-resolution Network）</news:title>
   <news:publication_date>2026-06-30T06:08:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/706474</loc>
  <lastmod>2026-06-30T06:08:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動スムージングは時系列分類を本当に改善するか（Can automated smoothing significantly improve benchmark time series classification algorithms?）</news:title>
   <news:publication_date>2026-06-30T06:08:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/706472</loc>
  <lastmod>2026-06-30T06:08:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートフォンでの歩容認識を現場で実現する（Deep Learning-Based Gait Recognition Using Smartphones in the Wild）</news:title>
   <news:publication_date>2026-06-30T06:08:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/706470</loc>
  <lastmod>2026-06-30T06:07:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>畳み込み再帰予測器によるマルチターゲット追跡の新展開（Convolutional Recurrent Predictor: Implicit Representation for Multi-target Filtering and Tracking）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-30T06:07:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>液体時定数リカレントニューラルネットワークの普遍近似性（Liquid Time-constant Recurrent Neural Networks as Universal Approximators）</news:title>
   <news:publication_date>2026-06-30T06:07:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-30T06:07:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>真空管（チューブ）アンプのエミュレーションに深層学習を使う意義（DEEP LEARNING FOR TUBE AMPLIFIER EMULATION）</news:title>
   <news:publication_date>2026-06-30T06:07:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-30T06:06:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>核融合研究への深層学習の応用（Applications of Deep Learning to Nuclear Fusion Research）</news:title>
   <news:publication_date>2026-06-30T06:06:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706462</loc>
  <lastmod>2026-06-30T05:15:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所ブロック座標降下法による畳み込みスパース符号化モデルの効率化（A Local Block Coordinate Descent Algorithm for the Convolutional Sparse Coding Model）</news:title>
   <news:publication_date>2026-06-30T05:15:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706460</loc>
  <lastmod>2026-06-30T05:15:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>雑音付きRectifierニューラルネットワークにおける深い信号伝播の臨界初期化（Critical initialisation for deep signal propagation in noisy rectifier neural networks）</news:title>
   <news:publication_date>2026-06-30T05:15:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706458</loc>
  <lastmod>2026-06-30T05:15:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模非ラベル音声データを用いた弱教師ありCRNNによる音響イベント検出（WEAKLY SUPERVISED CRNN SYSTEM FOR SOUND EVENT DETECTION WITH LARGE-SCALE UNLABELED IN-DOMAIN DATA）</news:title>
   <news:publication_date>2026-06-30T05:15:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706456</loc>
  <lastmod>2026-06-30T05:14:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非教師あり単語写像をMMD最大化で学ぶ（Learning Unsupervised Word Mapping by Maximizing Mean Discrepancy）</news:title>
   <news:publication_date>2026-06-30T05:14:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706454</loc>
  <lastmod>2026-06-30T05:14:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カプセルネットワークによる線形時間ニューラル機械翻訳（Towards Linear Time Neural Machine Translation with Capsule Networks）</news:title>
   <news:publication_date>2026-06-30T05:14:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706452</loc>
  <lastmod>2026-06-30T05:14:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数ドメイン辞書学習の効率化（EFFICIENT MULTI-DOMAIN DICTIONARY LEARNING WITH GANS）</news:title>
   <news:publication_date>2026-06-30T05:14:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706450</loc>
  <lastmod>2026-06-30T05:13:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層型長期同時記憶による対人行動認識（Hierarchical Long Short-Term Concurrent Memory for Human Interaction Recognition）</news:title>
   <news:publication_date>2026-06-30T05:13:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706448</loc>
  <lastmod>2026-06-30T04:23:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈から未知フレーズを説明する技術（Learning to Describe Unknown Phrases with Local and Global Contexts）</news:title>
   <news:publication_date>2026-06-30T04:23:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706446</loc>
  <lastmod>2026-06-30T04:22:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>代表カーネルを選ぶことで多様性を保ったカーネル結合を実現する手法（Multiple Kernel k-Means Clustering by Selecting Representative Kernels）</news:title>
   <news:publication_date>2026-06-30T04:22:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706444</loc>
  <lastmod>2026-06-30T04:22:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Horizon：Facebookのオープンソース応用強化学習プラットフォーム (Horizon: Facebook’s Open Source Applied Reinforcement Learning Platform)</news:title>
   <news:publication_date>2026-06-30T04:22:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706442</loc>
  <lastmod>2026-06-30T04:21:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>永続ホモロジーに基づく機械学習と応用（Persistent-Homology-based Machine Learning and its Applications – A Survey）</news:title>
   <news:publication_date>2026-06-30T04:21:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706440</loc>
  <lastmod>2026-06-30T04:21:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数の不正マイニングプールがもたらす脅威と遅延リスク（A Deep Dive into Blockchain Selfish Mining）</news:title>
   <news:publication_date>2026-06-30T04:21:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706438</loc>
  <lastmod>2026-06-30T04:21:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高欠損率に強いLasso（HMLasso: Lasso with High Missing Rate）</news:title>
   <news:publication_date>2026-06-30T04:21:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706436</loc>
  <lastmod>2026-06-30T04:21:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語非依存リプレゼンタによるニューラル機械翻訳の効率化（Language-Independent Representor for Neural Machine Translation）</news:title>
   <news:publication_date>2026-06-30T04:21:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706434</loc>
  <lastmod>2026-06-30T03:29:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フィルタ削減を幾何学的中央値で行う手法（Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration）</news:title>
   <news:publication_date>2026-06-30T03:29:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706432</loc>
  <lastmod>2026-06-30T03:29:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動生成ペアデータによるスケッチ→画像変換の評価（Examining Performance of Sketch-to-Image Translation Models with Multiclass Automatically Generated Paired Training Data）</news:title>
   <news:publication_date>2026-06-30T03:29:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706430</loc>
  <lastmod>2026-06-30T03:29:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークで公正性を達成する（FNNC: Achieving Fairness through Neural Networks）</news:title>
   <news:publication_date>2026-06-30T03:29:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706428</loc>
  <lastmod>2026-06-30T03:28:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>漸進的メモリバンクによるドメイン逐次適応（PROGRESSIVE MEMORY BANKS FOR INCREMENTAL DOMAIN ADAPTATION）</news:title>
   <news:publication_date>2026-06-30T03:28:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706426</loc>
  <lastmod>2026-06-30T03:28:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教科書問題へのマルチモーダル文脈グラフによる解法（Textbook Question Answering with Multi-modal Context Graph Understanding and Self-supervised Open-set Comprehension）</news:title>
   <news:publication_date>2026-06-30T03:28:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706424</loc>
  <lastmod>2026-06-30T03:28:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マンダリンと英語のコードスイッチ音声認識に対するエンドツーエンド解法（On the End-to-End Solution to Mandarin-English Code-switching Speech Recognition）</news:title>
   <news:publication_date>2026-06-30T03:28:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706422</loc>
  <lastmod>2026-06-30T03:27:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SARN: 注意機構で効率化した関係推論（SARN: Sequential Attention Relational Network）</news:title>
   <news:publication_date>2026-06-30T03:27:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706420</loc>
  <lastmod>2026-06-30T02:36:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>質問を用いた社会的学習（Social Learning with Questions）</news:title>
   <news:publication_date>2026-06-30T02:36:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706418</loc>
  <lastmod>2026-06-30T02:36:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語モデルの学習ダイナミクスを可視化するSVCCA（Understanding Learning Dynamics Of Language Models with SVCCA）</news:title>
   <news:publication_date>2026-06-30T02:36:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706416</loc>
  <lastmod>2026-06-30T02:36:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次的ガイディングネットワークと注意機構による画像キャプショニング（A SEQUENTIAL GUIDING NETWORK WITH ATTENTION FOR IMAGE CAPTIONING）</news:title>
   <news:publication_date>2026-06-30T02:36:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706414</loc>
  <lastmod>2026-06-30T02:35:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル音楽合成による柔軟な音色制御（NEURAL MUSIC SYNTHESIS FOR FLEXIBLE TIMBRE CONTROL）</news:title>
   <news:publication_date>2026-06-30T02:35:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706412</loc>
  <lastmod>2026-06-30T02:35:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模刺青画像検索のための同時検出とコンパクト表現学習（Tattoo Image Search at Scale: Joint Detection and Compact Representation Learning）</news:title>
   <news:publication_date>2026-06-30T02:35:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706410</loc>
  <lastmod>2026-06-30T02:35:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>META-DES.Oracle：動的アンサンブル選択のメタ学習と特徴選択（META-DES.Oracle: Meta-learning and feature selection for dynamic ensemble selection）</news:title>
   <news:publication_date>2026-06-30T02:35:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706408</loc>
  <lastmod>2026-06-30T02:35:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチラベル頑健因子分解オートエンコーダと薬物相互作用予測への応用 (Multi-Label Robust Factorization Autoencoder and its Application in Predicting Drug-Drug Interactions)</news:title>
   <news:publication_date>2026-06-30T02:35:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706406</loc>
  <lastmod>2026-06-30T01:43:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン学習を用いた統計的裁定のアルゴリズム（Online Learning Algorithms for Statistical Arbitrage）</news:title>
   <news:publication_date>2026-06-30T01:43:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706404</loc>
  <lastmod>2026-06-30T01:43:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Balanced SparsityによるGPU上での高速かつ高精度なDNN推論（Balanced Sparsity for Efficient DNN Inference on GPU）</news:title>
   <news:publication_date>2026-06-30T01:43:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706402</loc>
  <lastmod>2026-06-30T01:43:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>COGNI-NET: 脳波に基づく認知特徴学習による視覚知覚の再現（COGNI-NET: COGNITIVE FEATURE LEARNING THROUGH DEEP VISUAL PERCEPTION）</news:title>
   <news:publication_date>2026-06-30T01:43:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706400</loc>
  <lastmod>2026-06-30T01:43:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識グラフに高次ネットワーク効果を注入する手法（MOHONE: Modeling Higher Order Network Effects in Knowledge Graphs via Network Infused Embeddings）</news:title>
   <news:publication_date>2026-06-30T01:43:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706398</loc>
  <lastmod>2026-06-30T01:42:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分クリックで学ぶ多様なランキングのオンライン学習（Online Diverse Learning to Rank from Partial-Click Feedback）</news:title>
   <news:publication_date>2026-06-30T01:42:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706396</loc>
  <lastmod>2026-06-30T01:42:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セッションベース推薦にグラフニューラルネットワークを適用する意義（Session-based Recommendation with Graph Neural Networks）</news:title>
   <news:publication_date>2026-06-30T01:42:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706394</loc>
  <lastmod>2026-06-30T01:42:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説明可能な自然言語処理に向けた生成的説明フレームワーク（Towards Explainable NLP: A Generative Explanation Framework for Text Classification）</news:title>
   <news:publication_date>2026-06-30T01:42:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706392</loc>
  <lastmod>2026-06-30T00:50:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話者ダイアライゼーションのための有効なメトリック学習パイプライン設計（DESIGNING AN EFFECTIVE METRIC LEARNING PIPELINE FOR SPEAKER DIARIZATION）</news:title>
   <news:publication_date>2026-06-30T00:50:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706390</loc>
  <lastmod>2026-06-30T00:50:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-30T00:50:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706388</loc>
  <lastmod>2026-06-30T00:50:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層畳み込みニューラルネットワークによる少モード光ファイバのモード分解学習 (Learning to decompose the modes in few-mode fibers with deep convolutional neural network)</news:title>
   <news:publication_date>2026-06-30T00:50:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706386</loc>
  <lastmod>2026-06-30T00:49:35Z</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のベイズ的視点（A Bayesian Perspective of Convolutional Neural Networks through a Deconvolutional Generative Model）</news:title>
   <news:publication_date>2026-06-30T00:49:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706384</loc>
  <lastmod>2026-06-30T00:49:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話者認証の長さばらつきに強い深層セグメント注意埋め込み（Deep Segment Attentive Embedding for Duration Robust Speaker Verification）</news:title>
   <news:publication_date>2026-06-30T00:49:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706382</loc>
  <lastmod>2026-06-30T00:49:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交通ネットワーク速度予測におけるCapsNetとNLSTMの組合せの実務的意義（Forecasting Transportation Network Speed Using Deep Capsule Networks with Nested LSTM Models）</news:title>
   <news:publication_date>2026-06-30T00:49:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706380</loc>
  <lastmod>2026-06-30T00:49:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fluxによる実践的機械学習環境の革新（Fashionable Modelling with Flux）</news:title>
   <news:publication_date>2026-06-30T00:49:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706378</loc>
  <lastmod>2026-06-29T23:57:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PerceptionNetによる遅延センサーフュージョン（PerceptionNet: A Deep Convolutional Neural Network for Late Sensor Fusion）</news:title>
   <news:publication_date>2026-06-29T23:57:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706376</loc>
  <lastmod>2026-06-29T23:57:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Counterfactual Regret Minimization の意義と実務的インパクト（Deep Counterfactual Regret Minimization）</news:title>
   <news:publication_date>2026-06-29T23:57:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706374</loc>
  <lastmod>2026-06-29T23:56:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多重量化文を用いた自然言語推論モデルのストレステスト（Stress-Testing Neural Models of Natural Language Inference with Multiply-Quantified Sentences）</news:title>
   <news:publication_date>2026-06-29T23:56:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706372</loc>
  <lastmod>2026-06-29T23:56:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>評価システムの情報性設計（Designing Informative Rating Systems: Evidence from an Online Labor Market）</news:title>
   <news:publication_date>2026-06-29T23:56:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706370</loc>
  <lastmod>2026-06-29T23:56:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼度推定と削除予測における双方向再帰ニューラルネットワーク（CONFIDENCE ESTIMATION AND DELETION PREDICTION USING BIDIRECTIONAL RECURRENT NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-06-29T23:56:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706368</loc>
  <lastmod>2026-06-29T23:56:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>双方向ラティス再帰型ニューラルネットワークによる信頼度推定（BI-DIRECTIONAL LATTICE RECURRENT NEURAL NETWORKS FOR CONFIDENCE ESTIMATION）</news:title>
   <news:publication_date>2026-06-29T23:56:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706366</loc>
  <lastmod>2026-06-29T23:56:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散台帳設計の解読（Decrypting Distributed Ledger Design - Taxonomy, Classification and Blockchain Community Evaluation）</news:title>
   <news:publication_date>2026-06-29T23:56:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706364</loc>
  <lastmod>2026-06-29T23:05:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆最適化をオンラインで学ぶ手法（An Online-Learning Approach to Inverse Optimization）</news:title>
   <news:publication_date>2026-06-29T23:05:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706362</loc>
  <lastmod>2026-06-29T23:04:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速アップリンク割当のためのスリーピング・マルチアームド・バンディット学習（Sleeping Multi-Armed Bandit Learning for Fast Uplink Grant Allocation in Machine Type Communications）</news:title>
   <news:publication_date>2026-06-29T23:04:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706360</loc>
  <lastmod>2026-06-29T23:04:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Word Mover’s Embeddingによる文書表現の刷新（Word Mover’s Embedding: From Word2Vec to Document Embedding）</news:title>
   <news:publication_date>2026-06-29T23:04:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706358</loc>
  <lastmod>2026-06-29T23:03:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外部惑星の透過スペクトルを網羅するスケール可能な前方モデル格子（Fully scalable forward model grid of exoplanet transmission spectra）</news:title>
   <news:publication_date>2026-06-29T23:03:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706356</loc>
  <lastmod>2026-06-29T23:03:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線の病変検出を高精度化する領域分割融合手法（SDFN: Segmentation-based Deep Fusion Network for Thoracic Disease Classification in Chest X-ray Images）</news:title>
   <news:publication_date>2026-06-29T23:03:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706354</loc>
  <lastmod>2026-06-29T23:03:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-29T23:03:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706352</loc>
  <lastmod>2026-06-29T23:03:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合信号アーキテクチャによる畳み込みニューラルネットワークの加速（A mixed signal architecture for convolutional neural networks）</news:title>
   <news:publication_date>2026-06-29T23:03:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706350</loc>
  <lastmod>2026-06-29T22:12:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サーブを学習する：ロボットへの示教を効率化する新枠組み（Learning to Serve: an Experimental Study for a new Learning from Demonstrations Framework）</news:title>
   <news:publication_date>2026-06-29T22:12:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706348</loc>
  <lastmod>2026-06-29T22:11:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非構造化されたプロセス観測集合の整理に向けた多様体学習（Manifold Learning for Organizing Unstructured Sets of Process Observations）</news:title>
   <news:publication_date>2026-06-29T22:11:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706346</loc>
  <lastmod>2026-06-29T22:10:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CHEERS結果：NGC 3393の狭線領域におけるChandra X線分光（CHEERS Results from NGC 3393, III: Chandra X-ray Spectroscopy of the Narrow Line Region）</news:title>
   <news:publication_date>2026-06-29T22:10:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706344</loc>
  <lastmod>2026-06-29T22:10:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リコイルフリーなジェット軸とTMD断片化が示す新しいジェット形状の法則性（Phenomenology with a recoil-free jet axis: TMD fragmentation and the jet shape）</news:title>
   <news:publication_date>2026-06-29T22:10:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706342</loc>
  <lastmod>2026-06-29T22:10:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半径方向に分解したセミアナリティック銀河進化モデルと機械学習チューニング（Towards a radially-resolved semi-analytic model for the evolution of disc galaxies tuned with machine learning）</news:title>
   <news:publication_date>2026-06-29T22:10:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706340</loc>
  <lastmod>2026-06-29T22:09:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3色画像から銀河金属量を予測する畳み込みニューラルネットワーク（Using convolutional neural networks to predict galaxy metallicity from three-color images）</news:title>
   <news:publication_date>2026-06-29T22:09:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706338</loc>
  <lastmod>2026-06-29T22:09:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トピック別感情分析で政治的イデオロギーを見抜く（Topic-Specific Sentiment Analysis Can Help Identify Political Ideology）</news:title>
   <news:publication_date>2026-06-29T22:09:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706336</loc>
  <lastmod>2026-06-29T21:18:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DropBlockによる畳み込みネットワークの正則化（DropBlock: A regularization method for convolutional networks）</news:title>
   <news:publication_date>2026-06-29T21:18:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706334</loc>
  <lastmod>2026-06-29T21:17:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ汚染攻撃が暴くノード埋め込みの脆弱性（DATA POISONING ATTACK AGAINST UNSUPERVISED NODE EMBEDDING METHODS）</news:title>
   <news:publication_date>2026-06-29T21:17:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706332</loc>
  <lastmod>2026-06-29T21:17:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムネットワーク蒸留による探索促進（Exploration by Random Network Distillation）</news:title>
   <news:publication_date>2026-06-29T21:17:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706330</loc>
  <lastmod>2026-06-29T21:16:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LUCIDによるTimepix検出器の軌道上初期結果（First results from the LUCID-Timepix spacecraft payload onboard the TechDemoSat-1 satellite in Low Earth Orbit）</news:title>
   <news:publication_date>2026-06-29T21:16:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706328</loc>
  <lastmod>2026-06-29T21:16:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MPNA：畳み込みニューラルネットワーク向けデータフロー最適化を備えた大規模並列ニューラルアレイ（MPNA: A Massively-Parallel Neural Array Accelerator with Dataflow Optimization for Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-29T21:16:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706326</loc>
  <lastmod>2026-06-29T21:16:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スカラー場理論に対する回帰と生成ニューラルネットワーク（Regressive and generative neural networks for scalar field theory）</news:title>
   <news:publication_date>2026-06-29T21:16:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706324</loc>
  <lastmod>2026-06-29T21:15:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ボトムニウムの抑制に関する包括的記述（Global description of bottomonium suppression in proton-nucleus and nucleus-nucleus collisions at LHC energies）</news:title>
   <news:publication_date>2026-06-29T21:15:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706322</loc>
  <lastmod>2026-06-29T20:23:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然性、ハイパーボリック分岐と荷電ヒッグス検出の展望（Naturalness, the Hyperbolic Branch and Prospects for the Observation of Charged Higgs at High Luminosity LHC and 27 TeV LHC）</news:title>
   <news:publication_date>2026-06-29T20:23:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706320</loc>
  <lastmod>2026-06-29T20:23:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Total Variationを組み合わせた深層画像先験による画像復元（Image Restoration using Total Variation Regularized Deep Image Prior）</news:title>
   <news:publication_date>2026-06-29T20:23:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706318</loc>
  <lastmod>2026-06-29T20:22:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Divergence Networkによる発散関数の可視化手法（DIVERGENCE NETWORK: GRAPHICAL CALCULATION METHOD OF DIVERGENCE FUNCTIONS）</news:title>
   <news:publication_date>2026-06-29T20:22:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706316</loc>
  <lastmod>2026-06-29T20:22:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>資産価格分布と市場効率（Asset Price Distributions and Efficient Markets）</news:title>
   <news:publication_date>2026-06-29T20:22:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706314</loc>
  <lastmod>2026-06-29T20:21:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地下モデルにおける状態とパラメータの対応の発見（Discovering state-parameter mappings in subsurface models using generative adversarial networks）</news:title>
   <news:publication_date>2026-06-29T20:21:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706312</loc>
  <lastmod>2026-06-29T20:21:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汎用音声タグ付けにおけるCNNと統計特徴のアンサンブル（GENERAL AUDIO TAGGING WITH ENSEMBLING CONVOLUTIONAL NEURAL NETWORKS AND STATISTICAL FEATURES）</news:title>
   <news:publication_date>2026-06-29T20:21:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706310</loc>
  <lastmod>2026-06-29T20:21:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスリンガル文センテンス表現の学習（Learning Cross-Lingual Sentence Representations via a Multi-task Dual-Encoder Model）</news:title>
   <news:publication_date>2026-06-29T20:21:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706308</loc>
  <lastmod>2026-06-29T19:30:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク上の疫学プロセスの確率的最適制御（Stochastic Optimal Control of Epidemic Processes in Networks）</news:title>
   <news:publication_date>2026-06-29T19:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706306</loc>
  <lastmod>2026-06-29T19:29:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RGB-D物体検出のためのクロスモーダル注意文脈学習（Cross-Modal Attentional Context Learning for RGB-D Object Detection）</news:title>
   <news:publication_date>2026-06-29T19:29:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706304</loc>
  <lastmod>2026-06-29T19:29:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepTwistによるモデル圧縮の実務的インパクト（DEEPTWIST: LEARNING MODEL COMPRESSION VIA OCCASIONAL WEIGHT DISTORTION）</news:title>
   <news:publication_date>2026-06-29T19:29:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706302</loc>
  <lastmod>2026-06-29T19:28:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CLEASE：クラスター展開法の汎用的で使いやすい実装（CLEASE: A versatile and user-friendly implementation of Cluster Expansion method）</news:title>
   <news:publication_date>2026-06-29T19:28:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706300</loc>
  <lastmod>2026-06-29T19:28:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度航空画像の意味セグメンテーションのための文脈的アワーグラスネットワーク (Contextual Hourglass Network for Semantic Segmentation of High Resolution Aerial Imagery)</news:title>
   <news:publication_date>2026-06-29T19:28:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706298</loc>
  <lastmod>2026-06-29T19:28:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模有機結晶のバンドギャップ予測を機械学習で行う（Band gap prediction for large organic crystal structures with machine learning）</news:title>
   <news:publication_date>2026-06-29T19:28:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706296</loc>
  <lastmod>2026-06-29T19:28:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行動認識における未知検知を投票で解く（Informed Democracy: Voting-based Novelty Detection for Action Recognition）</news:title>
   <news:publication_date>2026-06-29T19:28:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706294</loc>
  <lastmod>2026-06-29T18:36:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>急性骨髄性白血病の予後予測に対する深層学習の応用（Application of Deep Learning on Predicting Prognosis of Acute Myeloid Leukemia with Cytogenetics, Age, and Mutations）</news:title>
   <news:publication_date>2026-06-29T18:36:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706292</loc>
  <lastmod>2026-06-29T18:35:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移可能な正負感情の音声認識を目指すクラス別敵対的ドメイン適応（TRANSFERABLE POSITIVE/NEGATIVE SPEECH EMOTION RECOGNITION VIA CLASS-WISE ADVERSARIAL DOMAIN ADAPTATION）</news:title>
   <news:publication_date>2026-06-29T18:35:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706290</loc>
  <lastmod>2026-06-29T18:34:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークの部分的強凸性が示す学習安定化の可能性（Piecewise Strong Convexity of Neural Networks）</news:title>
   <news:publication_date>2026-06-29T18:34:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706288</loc>
  <lastmod>2026-06-29T18:34:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚ベースの車線制御における深層学習と強化学習の統合（Reinforcement Learning and Deep Learning based Lateral Control for Autonomous Driving）</news:title>
   <news:publication_date>2026-06-29T18:34:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706286</loc>
  <lastmod>2026-06-29T18:34:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構を内蔵した再帰ユニットがもたらす変化（Recurrent Attention Unit）</news:title>
   <news:publication_date>2026-06-29T18:34:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706284</loc>
  <lastmod>2026-06-29T18:34:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療文献におけるPICO要素検出の高精度化（Advancing PICO Element Detection in Biomedical Text via Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-29T18:34:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706282</loc>
  <lastmod>2026-06-29T18:33:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチプレックス位相復元のスペクトル法（SPECTRAL METHOD FOR MULTIPLEXED PHASE RETRIEVAL AND APPLICATION IN OPTICAL IMAGING IN COMPLEX MEDIA）</news:title>
   <news:publication_date>2026-06-29T18:33:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706272</loc>
  <lastmod>2026-06-29T17:42:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>区間境界伝播（IBP）による検証可能な頑健モデルの訓練法（On the Effectiveness of Interval Bound Propagation for Training Veriﬁably Robust Models）</news:title>
   <news:publication_date>2026-06-29T17:42:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706270</loc>
  <lastmod>2026-06-29T17:33:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長短期注意（Long Short-Term Attention）</news:title>
   <news:publication_date>2026-06-29T17:33:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706268</loc>
  <lastmod>2026-06-29T17:33:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HTTPトラフィックの異常検知を言語モデルで実現するDeepHTTP（DeepHTTP: Semantics-Structure Model with Attention for Anomalous HTTP Traffic Detection and Pattern Mining）</news:title>
   <news:publication_date>2026-06-29T17:33:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706266</loc>
  <lastmod>2026-06-29T17:33:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程による条件付き確率密度推定（Gaussian Process Conditional Density Estimation）</news:title>
   <news:publication_date>2026-06-29T17:33:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706264</loc>
  <lastmod>2026-06-29T17:32:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタサイズ管理による多段階凝集型階層的クラスタリングの実務的改善（CLUSTER SIZE MANAGEMENT IN MULTI-STAGE AGGLOMERATIVE HIERARCHICAL CLUSTERING OF ACOUSTIC SPEECH SEGMENTS）</news:title>
   <news:publication_date>2026-06-29T17:32:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706262</loc>
  <lastmod>2026-06-29T17:32:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声セグメントクラスタリングのための特徴軌跡ダイナミックタイムワーピング（FEATURE TRAJECTORY DYNAMIC TIME WARPING FOR CLUSTERING OF SPEECH SEGMENTS）</news:title>
   <news:publication_date>2026-06-29T17:32:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706260</loc>
  <lastmod>2026-06-29T17:31:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジで動く音声理解の現実（Spoken Language Understanding on the Edge）</news:title>
   <news:publication_date>2026-06-29T17:31:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706258</loc>
  <lastmod>2026-06-29T16:40:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語質問応答における解釈可能性のための構成的注意ネットワーク（Compositional Attention Networks for Interpretability in Natural Language Question Answering）</news:title>
   <news:publication_date>2026-06-29T16:40:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706256</loc>
  <lastmod>2026-06-29T16:30:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハバードモデルの密度汎関数を機械学習で再構築する（Machine learning density functional theory for the Hubbard model）</news:title>
   <news:publication_date>2026-06-29T16:30:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706254</loc>
  <lastmod>2026-06-29T16:30:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個人のスマートフォン行動ルールを採掘する研究課題（Research Issues in Mining User Behavioral Rules for Context-Aware Intelligent Mobile Applications）</news:title>
   <news:publication_date>2026-06-29T16:30:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706252</loc>
  <lastmod>2026-06-29T16:28:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネルの再解釈と疑似ベイズ学習による特徴学習（Pseudo-Bayesian Learning with Kernel Fourier Transform as Prior）</news:title>
   <news:publication_date>2026-06-29T16:28:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706250</loc>
  <lastmod>2026-06-29T16:28:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間領域におけるスペクトル事前知識を用いたスパースガウス過程音声源分離（SPARSE GAUSSIAN PROCESS AUDIO SOURCE SEPARATION USING SPECTRUM PRIORS IN THE TIME-DOMAIN）</news:title>
   <news:publication_date>2026-06-29T16:28:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706248</loc>
  <lastmod>2026-06-29T16:28:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込み辞書正則化によるトモグラフィー再構成（CONVOLUTIONAL DICTIONARY REGULARIZERS FOR TOMOGRAPHIC INVERSION）</news:title>
   <news:publication_date>2026-06-29T16:28:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706246</loc>
  <lastmod>2026-06-29T16:28:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パルサー風星雲 HESS J1825–137 内の粒子輸送（Particle transport within the pulsar wind nebula HESS J1825–137）</news:title>
   <news:publication_date>2026-06-29T16:28:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706244</loc>
  <lastmod>2026-06-29T15:36:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>障害のある発話のための非並列音声変換に関するGAN研究（Generative Adversarial Networks for Unpaired Voice Transformation on Impaired Speech）</news:title>
   <news:publication_date>2026-06-29T15:36:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706242</loc>
  <lastmod>2026-06-29T15:36:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-29T15:36:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706240</loc>
  <lastmod>2026-06-29T15:35:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-29T15:35:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706238</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地域間・タスク間の知識移転による適応的転移学習（Adaptive Transfer Learning in Deep Neural Networks: Wind Power Prediction using Knowledge Transfer from Region to Region and Between Different Task Domains）</news:title>
   <news:publication_date>2026-06-29T15:35:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトウェア製品の機能選定における利害関係者の価値命題（Key Stakeholders’ Value Propositions for Feature Selection in Software-intensive Products）</news:title>
   <news:publication_date>2026-06-29T15:35:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706234</loc>
  <lastmod>2026-06-29T15:34:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピッチ同期マルチスケールGANによる音声波形生成（WAVEFORM GENERATION FOR TEXT-TO-SPEECH SYNTHESIS USING PITCH-SYNCHRONOUS MULTI-SCALE GENERATIVE ADVERSARIAL NETWORKS）</news:title>
   <news:publication_date>2026-06-29T15:34:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706232</loc>
  <lastmod>2026-06-29T15:34:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SubSpectralNet：周波数帯ごとの特徴抽出で音環境を識別する新手法（SubSpectralNet – Using Sub-spectrogram Based Convolutional Neural Networks for Acoustic Scene Classification）</news:title>
   <news:publication_date>2026-06-29T15:34:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706230</loc>
  <lastmod>2026-06-29T14:43:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大西洋サケの深潜行動（Deep-diving of Atlantic Salmon）</news:title>
   <news:publication_date>2026-06-29T14:43:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706228</loc>
  <lastmod>2026-06-29T14:43:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次的深層モデルによる知識グラフ補完（DSKG: A Deep Sequential Model for Knowledge Graph Completion）</news:title>
   <news:publication_date>2026-06-29T14:43:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706226</loc>
  <lastmod>2026-06-29T14:43:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習ベースの予測制御の統一的アプローチ（Learning-based predictive control for linear systems: a unitary approach）</news:title>
   <news:publication_date>2026-06-29T14:43:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706224</loc>
  <lastmod>2026-06-29T14:42:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>談話表現構造のためのニューラルパーシングの探究 (Exploring Neural Methods for Parsing Discourse Representation Structures)</news:title>
   <news:publication_date>2026-06-29T14:42:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706222</loc>
  <lastmod>2026-06-29T14:42:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形深層回帰による多次元信号の予測と画像符号化への応用（NONLINEAR PREDICTION OF MULTIDIMENSIONAL SIGNALS VIA DEEP REGRESSION WITH APPLICATIONS TO IMAGE CODING）</news:title>
   <news:publication_date>2026-06-29T14:42:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706220</loc>
  <lastmod>2026-06-29T14:41:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対者批評者を用いたネットワークのロバスト性向上（Improved Network Robustness with Adversary Critic）</news:title>
   <news:publication_date>2026-06-29T14:41:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706218</loc>
  <lastmod>2026-06-29T14:41:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル近傍ネットワーク（Neural Nearest Neighbors Networks）</news:title>
   <news:publication_date>2026-06-29T14:41:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706216</loc>
  <lastmod>2026-06-29T13:50:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ADEPOSによる予知保全向け省電力異常検知（ADEPOS: Anomaly Detection Based Power Saving for Predictive Maintenance using Edge Computing）</news:title>
   <news:publication_date>2026-06-29T13:50:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706214</loc>
  <lastmod>2026-06-29T13:30:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極少データでほぼ教師なし音声認識を実現する方法（ALMOST-UNSUPERVISED SPEECH RECOGNITION WITH CLOSE-TO-ZERO RESOURCE）</news:title>
   <news:publication_date>2026-06-29T13:30:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706212</loc>
  <lastmod>2026-06-29T13:29:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短縮空間・スペクトルRNNと並列GRUによるハイパースペクトル画像分類（Shorten Spatial-spectral RNN with Parallel-GRU for Hyperspectral Image Classification）</news:title>
   <news:publication_date>2026-06-29T13:29:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706210</loc>
  <lastmod>2026-06-29T13:29:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>英越間ニューラル機械翻訳の実証研究（NEURAL MACHINE TRANSLATION BETWEEN VIETNAMESE AND ENGLISH: AN EMPIRICAL STUDY）</news:title>
   <news:publication_date>2026-06-29T13:29:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706208</loc>
  <lastmod>2026-06-29T13:28:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数箇所のプログラム修復戦略の学習（Multi-Location Program Repair Strategies Learned from Past Successful Experience）</news:title>
   <news:publication_date>2026-06-29T13:28:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706206</loc>
  <lastmod>2026-06-29T13:28:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オフポリシーActor‑Criticにおける相対重要度サンプリング（Relative Importance Sampling for off-Policy Actor-Critic in Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-29T13:28:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706204</loc>
  <lastmod>2026-06-29T13:28:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UnityとPythonによる自動運転車の3D交通シミュレーション (3D Traffic Simulation for Autonomous Vehicles in Unity and Python)</news:title>
   <news:publication_date>2026-06-29T13:28:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706202</loc>
  <lastmod>2026-06-29T12:36:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>次元を越える位相の接続：1D Zak相から2D チェルン数へ（The Connection of Topology between Systems with Different Dimensions: 1D Zak Phases to 2D Chern Number, Weyl Point as the Jumping Channel for One Singularity and Nodal Line to Merge All Singularities）</news:title>
   <news:publication_date>2026-06-29T12:36:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706200</loc>
  <lastmod>2026-06-29T12:36:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情目標を組み込むソフトウェア設計の体系化（Emotionalism within People-Oriented Software Design）</news:title>
   <news:publication_date>2026-06-29T12:36:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706198</loc>
  <lastmod>2026-06-29T12:36:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタ間類似度の高速伝播による強化型アンサンブルクラスタリング（Enhanced Ensemble Clustering via Fast Propagation of Cluster-wise Similarities）</news:title>
   <news:publication_date>2026-06-29T12:36:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706196</loc>
  <lastmod>2026-06-29T12:35:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒューマノイドロボットの共同行為ジェスチャ生成（Co-Speech Gesture Generation for Humanoid Robots）</news:title>
   <news:publication_date>2026-06-29T12:35:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706194</loc>
  <lastmod>2026-06-29T12:35:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム時系列スキップによるマルチレート動画解析（Random Temporal Skipping for Multirate Video Analysis）</news:title>
   <news:publication_date>2026-06-29T12:35:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706192</loc>
  <lastmod>2026-06-29T12:34:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像キャプショニングのゲーテッド階層型注意機構（Gated Hierarchical Attention for Image Captioning）</news:title>
   <news:publication_date>2026-06-29T12:34:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706190</loc>
  <lastmod>2026-06-29T11:43:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機能選択で転移学習を変える：Gated Transfer Network（Gated Transfer Network for Transfer Learning）</news:title>
   <news:publication_date>2026-06-29T11:43:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706188</loc>
  <lastmod>2026-06-29T11:43:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepGRU：軽量で実運用向けのジェスチャ認識ユーティリティ（DeepGRU: Deep Gesture Recognition Utility）</news:title>
   <news:publication_date>2026-06-29T11:43:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706186</loc>
  <lastmod>2026-06-29T11:42:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラス不均衡下における弱監視での深層表現学習（Weak-supervision for Deep Representation Learning under Class Imbalance）</news:title>
   <news:publication_date>2026-06-29T11:42:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706184</loc>
  <lastmod>2026-06-29T11:42:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模なコントロールバリアント群を用いた変分推論の改善（Using Large Ensembles of Control Variates for Variational Inference）</news:title>
   <news:publication_date>2026-06-29T11:42:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706182</loc>
  <lastmod>2026-06-29T11:42:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DARKMENTIONによる企業狙いの外部サイバー攻撃予測（DARKMENTION: A Deployed System to Predict Enterprise-Targeted External Cyberattacks）</news:title>
   <news:publication_date>2026-06-29T11:42:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706180</loc>
  <lastmod>2026-06-29T11:41:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続学習評価の再検討 — 強力なベースラインの重要性（Re-evaluating Continual Learning Scenarios: A Categorization and Case for Strong Baselines）</news:title>
   <news:publication_date>2026-06-29T11:41:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706178</loc>
  <lastmod>2026-06-29T11:41:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的汎用交通シーン予測の枠組み（A Framework for Probabilistic Generic Traffic Scene Prediction）</news:title>
   <news:publication_date>2026-06-29T11:41:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706176</loc>
  <lastmod>2026-06-29T10:50:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周波数領域/画像領域を組み合わせたMRI再構成のハイブリッド深層ネットワーク（A Hybrid Frequency-domain/Image-domain Deep Network for Magnetic Resonance Image Reconstruction）</news:title>
   <news:publication_date>2026-06-29T10:50:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-06-29T10:50:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴マップフィルタリングによる視覚的場所認識の改善（Feature Map Filtering: Improving Visual Place Recognition with Convolutional Calibration）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/706172</loc>
  <lastmod>2026-06-29T10:49:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>貪欲法を微分可能にするネットワーク：Differentiable Greedy Networks（Differentiable Greedy Networks）</news:title>
   <news:publication_date>2026-06-29T10:49:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706170</loc>
  <lastmod>2026-06-29T10:49:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子化された行列補完に対するHuber損失を用いた新手法（A Novel Approach to Quantized Matrix Completion Using Huber Loss Measure）</news:title>
   <news:publication_date>2026-06-29T10:49:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706168</loc>
  <lastmod>2026-06-29T10:48:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>通信制約下における分散凸最適化の考え方（DISTRIBUTED CONVEX OPTIMIZATION WITH LIMITED COMMUNICATIONS）</news:title>
   <news:publication_date>2026-06-29T10:48:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706166</loc>
  <lastmod>2026-06-29T10:48:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シンプルな繰り返しユニットと縮約テンソル積表現（A SIMPLE RECURRENT UNIT WITH REDUCED TENSOR PRODUCT REPRESENTATIONS）</news:title>
   <news:publication_date>2026-06-29T10:48:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706164</loc>
  <lastmod>2026-06-29T10:48:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ダンスを教えるロボットが示した「身体と認知の融合」—学習支援における適応的インピーダンス制御の提案（Dance Teaching by a Robot: Combining Cognitive and Physical Human–Robot Interaction for Supporting the Skill Learning Process）</news:title>
   <news:publication_date>2026-06-29T10:48:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706162</loc>
  <lastmod>2026-06-29T09:56:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模n・pベイズスパース回帰における事前条件付き共役勾配法によるギブスサンプリング加速（Prior-preconditioned Conjugate Gradient Method for Accelerated Gibbs Sampling in &amp;#039;Large n &amp;amp; Large p&amp;#039; Bayesian Sparse Regression）</news:title>
   <news:publication_date>2026-06-29T09:56:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706160</loc>
  <lastmod>2026-06-29T09:49:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NGC 3221周辺の大質量ウォームホット周囲銀河媒質の証拠 (Evidence for massive warm-hot circumgalactic medium around NGC 3221)</news:title>
   <news:publication_date>2026-06-29T09:49:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706158</loc>
  <lastmod>2026-06-29T09:48:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語内部構造のより良い学習法（Learning Better Internal Structure of Words for Sequence Labeling）</news:title>
   <news:publication_date>2026-06-29T09:48:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706156</loc>
  <lastmod>2026-06-29T09:47:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模リモートセンシングデータのセマンティックセグメンテーションに対する増分学習（Incremental Learning for Semantic Segmentation of Large-Scale Remote Sensing Data）</news:title>
   <news:publication_date>2026-06-29T09:47:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706154</loc>
  <lastmod>2026-06-29T09:47:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地平の呪いを破る：無限ホライズンでのオフポリシー推定（Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation）</news:title>
   <news:publication_date>2026-06-29T09:47:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706152</loc>
  <lastmod>2026-06-29T09:47:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列注意機構によるニューラル機械翻訳の高速化と精度向上（Parallel Attention Mechanisms in Neural Machine Translation）</news:title>
   <news:publication_date>2026-06-29T09:47:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706150</loc>
  <lastmod>2026-06-29T09:46:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>参加者の満足度を考慮したライフタイム最適化（Stay With Me: Lifetime Maximization Through Heteroscedastic Linear Bandits With Reneging）</news:title>
   <news:publication_date>2026-06-29T09:46:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706148</loc>
  <lastmod>2026-06-29T08:55:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルネットワークにおけるボット検出と影響評価（Detecting Bots and Assessing Their Impact）</news:title>
   <news:publication_date>2026-06-29T08:55:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706146</loc>
  <lastmod>2026-06-29T08:55:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビッグデータとサイバーフィジカルシステムの全景（Big Data Meet Cyber-Physical Systems: A Panoramic Survey）</news:title>
   <news:publication_date>2026-06-29T08:55:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706144</loc>
  <lastmod>2026-06-29T08:55:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大語彙ニューラル言語モデルの高速ソフトマックス推論法（LEARNING TO SCREEN FOR FAST SOFTMAX INFERENCE ON LARGE VOCABULARY NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-06-29T08:55:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706142</loc>
  <lastmod>2026-06-29T08:54:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>準同型暗号における条件分岐と機械学習応用（Conditionals in Homomorphic Encryption, and Machine Learning Applications）</news:title>
   <news:publication_date>2026-06-29T08:54:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706140</loc>
  <lastmod>2026-06-29T08:54:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒルベルト空間での学習と推論：量子グラフィカルモデルの再解釈（Learning and Inference in Hilbert Space with Quantum Graphical Models）</news:title>
   <news:publication_date>2026-06-29T08:54:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706138</loc>
  <lastmod>2026-06-29T08:53:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習のヒューリスティクスを詳述する（A Closer Look at Deep Learning Heuristics: Learning Rate Restarts, Warmup and Distillation）</news:title>
   <news:publication_date>2026-06-29T08:53:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706136</loc>
  <lastmod>2026-06-29T08:53:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セメム専門家の疎な積による言語モデリング (Language Modeling with Sparse Product of Sememe Experts)</news:title>
   <news:publication_date>2026-06-29T08:53:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706134</loc>
  <lastmod>2026-06-29T08:02:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行動コード化のためのマルチラベル・マルチタスク深層学習（Multi-label Multi-task Deep Learning for Behavioral Coding）</news:title>
   <news:publication_date>2026-06-29T08:02:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706132</loc>
  <lastmod>2026-06-29T07:53:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地名解析評価の実用的ガイド（A Pragmatic Guide to Geoparsing Evaluation）</news:title>
   <news:publication_date>2026-06-29T07:53:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706130</loc>
  <lastmod>2026-06-29T07:53:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散化拡散過程による非凸最適化の全局解探索（Global Non-convex Optimization with Discretized Diffusions）</news:title>
   <news:publication_date>2026-06-29T07:53:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706128</loc>
  <lastmod>2026-06-29T07:52:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セルラー環境で遅延を制御するTCP、C2TCPの本質（C2TCP: A Flexible Cellular TCP to Meet Stringent Delay Requirements）</news:title>
   <news:publication_date>2026-06-29T07:52:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706126</loc>
  <lastmod>2026-06-29T07:52:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>薄明宇宙の微量金属測定（EMISSION LINE METALLICITIES FROM THE FAINT INFRARED GRISM SURVEY AND VLT/MUSE）</news:title>
   <news:publication_date>2026-06-29T07:52:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706124</loc>
  <lastmod>2026-06-29T07:52:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高赤方偏移サブミリ波銀河におけるらせん腕・棒・環の証拠（ALMA Reveals Potential Evidence for Spiral Arms, Bars, and Rings in High-Redshift Submillimeter Galaxies）</news:title>
   <news:publication_date>2026-06-29T07:52:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706122</loc>
  <lastmod>2026-06-29T07:51:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>要約モデルにおける内容選択の理解（Content Selection in Deep Learning Models of Summarization）</news:title>
   <news:publication_date>2026-06-29T07:51:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706120</loc>
  <lastmod>2026-06-29T07:00:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>導関数を含むガウス過程回帰の大規模化（Scaling Gaussian Process Regression with Derivatives）</news:title>
   <news:publication_date>2026-06-29T07:00:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706118</loc>
  <lastmod>2026-06-29T06:59:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み減衰による正則化の三つの仕組み（THREE MECHANISMS OF WEIGHT DECAY REGULARIZATION）</news:title>
   <news:publication_date>2026-06-29T06:59:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706116</loc>
  <lastmod>2026-06-29T06:59:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習における汎化の評価（Assessing Generalization in Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-29T06:59:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706114</loc>
  <lastmod>2026-06-29T06:58:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークにおける不確実性推定の原理的アプローチ（Towards Principled Uncertainty Estimation for Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-29T06:58:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706112</loc>
  <lastmod>2026-06-29T06:58:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザー生成データを活用したコメント生成の学習 (Learning Comment Generation by Leveraging User-Generated Data)</news:title>
   <news:publication_date>2026-06-29T06:58:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706110</loc>
  <lastmod>2026-06-29T06:58:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一様分布下での敵対的リスクと堅牢性の定義と含意（Adversarial Risk and Robustness: General Definitions and Implications for the Uniform Distribution）</news:title>
   <news:publication_date>2026-06-29T06:58:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706108</loc>
  <lastmod>2026-06-29T06:58:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カルマン勾配降下法（Kalman Gradient Descent: Adaptive Variance Reduction in Stochastic Optimization）</news:title>
   <news:publication_date>2026-06-29T06:58:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706106</loc>
  <lastmod>2026-06-29T06:06:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PAC-Bayesian境界を最小化して学習するガウス過程（Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds）</news:title>
   <news:publication_date>2026-06-29T06:06:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706104</loc>
  <lastmod>2026-06-29T06:06:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低線量CT再構成を変える「画像マニフォールド」手法（Low dose CT reconstruction assisted by an image manifold prior）</news:title>
   <news:publication_date>2026-06-29T06:06:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706102</loc>
  <lastmod>2026-06-29T06:05:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MAESTROデータセットによるピアノ音楽生成の革新（Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset）</news:title>
   <news:publication_date>2026-06-29T06:05:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706100</loc>
  <lastmod>2026-06-29T06:05:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数ショットで挑む3D多モーダル医用画像分割（Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning）</news:title>
   <news:publication_date>2026-06-29T06:05:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706098</loc>
  <lastmod>2026-06-29T06:05:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習によるGMsFEM離散化の予測（Prediction of Discretization of GMsFEM using Deep Learning）</news:title>
   <news:publication_date>2026-06-29T06:05:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706096</loc>
  <lastmod>2026-06-29T06:04:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類と適応提案を組み合わせた近似ベイズ推論（Approximate Bayesian Computation via Population Monte Carlo and Classification）</news:title>
   <news:publication_date>2026-06-29T06:04:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706094</loc>
  <lastmod>2026-06-29T06:04:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ支援型構造故障同定（Data-assisted structural fault identification）</news:title>
   <news:publication_date>2026-06-29T06:04:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706092</loc>
  <lastmod>2026-06-29T05:13:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習ハイパーヒューリスティックによるマルチ目的最適化の単点探索応用（A Reinforcement Learning Hyper‑Heuristic in Multi‑Objective Single Point Search）</news:title>
   <news:publication_date>2026-06-29T05:13:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706090</loc>
  <lastmod>2026-06-29T05:13:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>夢を見るニューラルネットワーク：不要な記憶の忘却と重要な記憶の強化（Dreaming neural networks: forgetting spurious memories and reinforcing pure ones）</news:title>
   <news:publication_date>2026-06-29T05:13:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706088</loc>
  <lastmod>2026-06-29T05:13:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習が明かす宇宙の新情報（Machine learning uncovers new cosmological information）</news:title>
   <news:publication_date>2026-06-29T05:13:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706086</loc>
  <lastmod>2026-06-29T05:12:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Learning as a Serviceフレームワーク比較測定研究（A Comparative Measurement Study of Deep Learning as a Service Framework）</news:title>
   <news:publication_date>2026-06-29T05:12:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706084</loc>
  <lastmod>2026-06-29T05:12:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的バンディットに対する報酬操作攻撃（Adversarial Attacks on Stochastic Bandits）</news:title>
   <news:publication_date>2026-06-29T05:12:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706082</loc>
  <lastmod>2026-06-29T05:12:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReviewQA—関係性に基づくアスペクト別意見読解データセット (ReviewQA: a relational aspect-based opinion reading dataset)</news:title>
   <news:publication_date>2026-06-29T05:12:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706080</loc>
  <lastmod>2026-06-29T05:12:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピラミッド型Person Re-IDと動的マルチロス学習（Pyramidal Person Re-Identification via Multi-Loss Dynamic Training）</news:title>
   <news:publication_date>2026-06-29T05:12:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706078</loc>
  <lastmod>2026-06-29T04:21:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepSphere：HEALPixサンプリングを用いた効率的球面畳み込みニューラルネットワーク（DeepSphere: Efficient spherical Convolutional Neural Network with HEALPix sampling for cosmological applications）</news:title>
   <news:publication_date>2026-06-29T04:21:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706076</loc>
  <lastmod>2026-06-29T04:21:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波形ドメインでのエンドツーエンド音楽源分離は可能か（End-to-end music source separation: is it possible in the waveform domain?）</news:title>
   <news:publication_date>2026-06-29T04:21:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706074</loc>
  <lastmod>2026-06-29T04:21:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓MRIの動きによるアーチファクトを自動検出するCNN手法（Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning）</news:title>
   <news:publication_date>2026-06-29T04:21:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706072</loc>
  <lastmod>2026-06-29T04:20:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声と表情を同時に変換する技術の要点（Audiovisual Speaker Conversion: Jointly and Simultaneously Transforming Facial Expression and Acoustic Characteristics）</news:title>
   <news:publication_date>2026-06-29T04:20:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706070</loc>
  <lastmod>2026-06-29T04:19:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆問題のためのマルチスケール畳み込みニューラルネットワーク (Multi-scale Convolutional Neural Networks for Inverse Problems)</news:title>
   <news:publication_date>2026-06-29T04:19:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706068</loc>
  <lastmod>2026-06-29T04:19:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師なし学習による人間行動推定（Semi-unsupervised Learning of Human Activity using Deep Generative Models）</news:title>
   <news:publication_date>2026-06-29T04:19:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706066</loc>
  <lastmod>2026-06-29T04:19:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンピュータモデルの変分較正（Variational Calibration of Computer Models）</news:title>
   <news:publication_date>2026-06-29T04:19:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706064</loc>
  <lastmod>2026-06-29T03:28:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈を意識した音声認識における『難しいネガティブ例』を使った学習（Contextual Speech Recognition with Difficult Negative Training Examples）</news:title>
   <news:publication_date>2026-06-29T03:28:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706062</loc>
  <lastmod>2026-06-29T03:27:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲノムとメタゲノムの相互作用を高速に解析する手法（Fast Computation of Genome-Metagenome Interaction Effects）</news:title>
   <news:publication_date>2026-06-29T03:27:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706060</loc>
  <lastmod>2026-06-29T03:27:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフニューラルネットワークにおける中央値活性化関数（MEDIAN ACTIVATION FUNCTIONS FOR GRAPH NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-06-29T03:27:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706058</loc>
  <lastmod>2026-06-29T03:26:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルベース能動探索（Model-Based Active eXploration）</news:title>
   <news:publication_date>2026-06-29T03:26:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706056</loc>
  <lastmod>2026-06-29T03:26:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低複雑度RNNを用いた極性符号デコーダと重み量子化の実践的解説（LOW-COMPLEXITY RECURRENT NEURAL NETWORK-BASED POLAR DECODER WITH WEIGHT QUANTIZATION MECHANISM）</news:title>
   <news:publication_date>2026-06-29T03:26:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706054</loc>
  <lastmod>2026-06-29T03:26:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波ネットワークによる無向グラフでの長距離情報学習（Deep learning long-range information in undirected graphs with wave networks）</news:title>
   <news:publication_date>2026-06-29T03:26:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706052</loc>
  <lastmod>2026-06-29T03:26:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正則化付き最尤推定による混合エキスパートモデルの変革（Regularized Maximum Likelihood Estimation and Feature Selection in Mixtures-of-Experts Models）</news:title>
   <news:publication_date>2026-06-29T03:26:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706050</loc>
  <lastmod>2026-06-29T02:35:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同時ワイヤレス情報・電力伝送を学習で設計する（A Learning Approach to Wireless Information and Power Transfer）</news:title>
   <news:publication_date>2026-06-29T02:35:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706048</loc>
  <lastmod>2026-06-29T02:34:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イメージに基づくサンプル構築によるゼロショット学習（Imagination Based Sample Construction for Zero-Shot Learning）</news:title>
   <news:publication_date>2026-06-29T02:34:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706046</loc>
  <lastmod>2026-06-29T02:34:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークによる音楽のオーディオ・インペインティング（AUDIO INPAINTING OF MUSIC BY MEANS OF NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-06-29T02:34:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706044</loc>
  <lastmod>2026-06-29T02:34:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子層堆積による高アスペクト比イリジウムX線回折格子の作製（Towards Sub-micrometer High Aspect Ratio X-ray Gratings by Atomic Layer Deposition of Iridium）</news:title>
   <news:publication_date>2026-06-29T02:34:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706042</loc>
  <lastmod>2026-06-29T02:33:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>段階的機械学習によるエンティティ解決（Gradual Machine Learning for Entity Resolution）</news:title>
   <news:publication_date>2026-06-29T02:33:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706040</loc>
  <lastmod>2026-06-29T02:33:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相ハーモニック相関と畳み込みニューラルネットワーク（Phase Harmonic Correlations and Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-29T02:33:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706038</loc>
  <lastmod>2026-06-29T02:33:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バースト画像の自動選別で画質を最大化する手法（Burst ranking for blind multi-image deblurring）</news:title>
   <news:publication_date>2026-06-29T02:33:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706036</loc>
  <lastmod>2026-06-29T01:41:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遺伝子発現から薬物応答を予測する協調フィルタリング手法（FROM GENE EXPRESSION TO DRUG RESPONSE: A COLLABORATIVE FILTERING APPROACH）</news:title>
   <news:publication_date>2026-06-29T01:41:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706034</loc>
  <lastmod>2026-06-29T01:40:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動車精密部品の欠陥検出を統合した深層ネットワーク（PartsNet: A Unified Deep Network for Automotive Engine Precision Parts Defect Detection）</news:title>
   <news:publication_date>2026-06-29T01:40:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706032</loc>
  <lastmod>2026-06-29T01:32:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理学研究の進化を予測する機械学習（Using Machine Learning to Predict the Evolution of Physics Research）</news:title>
   <news:publication_date>2026-06-29T01:32:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706030</loc>
  <lastmod>2026-06-29T01:32:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的損失関数で学ぶ「教えること」の自動化（Learning to Teach with Dynamic Loss Functions）</news:title>
   <news:publication_date>2026-06-29T01:32:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706028</loc>
  <lastmod>2026-06-29T01:31:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰型ニューラルネットワークの訓練収束率に関する理論的進展（On the Convergence Rate of Training Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-06-29T01:31:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/706026</loc>
  <lastmod>2026-06-29T01:30:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構付きSeq2Seqモデルによる音声合成の話し方スタイル適応（SPEAKING STYLE ADAPTATION IN TEXT-TO-SPEECH SYNTHESIS USING SEQUENCE-TO-SEQUENCE MODELS WITH ATTENTION）</news:title>
   <news:publication_date>2026-06-29T01:30:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706024</loc>
  <lastmod>2026-06-29T01:30:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続学習における「条件付きリプレイ」と「周辺（マージナル）リプレイ」の比較（Marginal Replay vs Conditional Replay for Continual Learning）</news:title>
   <news:publication_date>2026-06-29T01:30:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706022</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パッチベースのスパース表現による細菌検出（PATCH-BASED SPARSE REPRESENTATION FOR BACTERIAL DETECTION）</news:title>
   <news:publication_date>2026-06-29T00:39:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706020</loc>
  <lastmod>2026-06-29T00:39:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的再ランク付けによるテキストスポッティングの改善（Visual Re-ranking with Natural Language Understanding for Text Spotting）</news:title>
   <news:publication_date>2026-06-29T00:39:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706018</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロジットペアリング手法は勾配ベース攻撃を欺ける（Logit Pairing Methods Can Fool Gradient-Based Attacks）</news:title>
   <news:publication_date>2026-06-29T00:38:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706016</loc>
  <lastmod>2026-06-29T00:37:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習におけるソフトウェア工学上の課題（Software Engineering Challenges of Deep Learning）</news:title>
   <news:publication_date>2026-06-29T00:37:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706014</loc>
  <lastmod>2026-06-29T00:37:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>明示的なユーザー・アイテム相互作用を組み込んだ深層強化学習による推薦（Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling）</news:title>
   <news:publication_date>2026-06-29T00:37:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706012</loc>
  <lastmod>2026-06-29T00:37:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カスケード型CNN-resBiLSTM-CTC：音声認識のためのエンドツーエンド音響モデル (CASCADED CNN-resBiLSTM-CTC: AN END-TO-END ACOUSTIC MODEL FOR SPEECH RECOGNITION)</news:title>
   <news:publication_date>2026-06-29T00:37:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706010</loc>
  <lastmod>2026-06-29T00:37:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepSymmetry によるタンデム反復と内部対称性の検出（DeepSymmetry: Using 3D convolutional networks for identification of tandem repeats and internal symmetries in protein structures）</news:title>
   <news:publication_date>2026-06-29T00:37:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706008</loc>
  <lastmod>2026-06-28T23:46:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトル変動に対処する拡張線形混合モデル（An Augmented Linear Mixing Model to Address Spectral Variability for Hyperspectral Unmixing）</news:title>
   <news:publication_date>2026-06-28T23:46:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706006</loc>
  <lastmod>2026-06-28T23:45:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型とデータ同化を組み合わせた物理過程の同定（Identification of physical processes via combined data-driven and data-assimilation methods）</news:title>
   <news:publication_date>2026-06-28T23:45:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706004</loc>
  <lastmod>2026-06-28T23:45:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GOT-10k：大規模高多様性トラッキングベンチマーク（GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the Wild）</news:title>
   <news:publication_date>2026-06-28T23:45:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706002</loc>
  <lastmod>2026-06-28T23:45:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴量バギングによるステガノグラファー識別（Feature Bagging for Steganographer Identification）</news:title>
   <news:publication_date>2026-06-28T23:45:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706000</loc>
  <lastmod>2026-06-28T23:45:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半クラウドソース型深層生成モデルによるクラスタリング（Semi-crowdsourced Clustering with Deep Generative Models）</news:title>
   <news:publication_date>2026-06-28T23:45:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705998</loc>
  <lastmod>2026-06-28T23:44:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Softmaxに替わる制御可能なスパースな代替手法（On Controllable Sparse Alternatives to Softmax）</news:title>
   <news:publication_date>2026-06-28T23:44:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705996</loc>
  <lastmod>2026-06-28T23:44:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-28T23:44:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705994</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>古典と量子機械学習の融合による肺がんサブタイプ分類（An Amalgamation of Classical and Quantum Machine Learning For the Classification of Adenocarcinoma and Squamous Cell Carcinoma Patients）</news:title>
   <news:publication_date>2026-06-28T22:53:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705992</loc>
  <lastmod>2026-06-28T22:52:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-28T22:52:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705990</loc>
  <lastmod>2026-06-28T22:52:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化する自己表現モデルによる部分空間クラスタリング（Evolutionary Self-Expressive Models for Subspace Clustering）</news:title>
   <news:publication_date>2026-06-28T22:52:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705988</loc>
  <lastmod>2026-06-28T22:52:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-28T22:52:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705986</loc>
  <lastmod>2026-06-28T22:52:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビットコイン上の実体（エンティティ）識別の実務的インパクト（Characterizing Entities in the Bitcoin Blockchain）</news:title>
   <news:publication_date>2026-06-28T22:52:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705984</loc>
  <lastmod>2026-06-28T22:51:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-28T22:51:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705982</loc>
  <lastmod>2026-06-28T22:51:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構に基づく車両追跡手法（Attention-Mechanism-based Tracking Method for Intelligent Internet of Vehicles）</news:title>
   <news:publication_date>2026-06-28T22:51:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705980</loc>
  <lastmod>2026-06-28T22:00:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>STFTスペクトル損失による音声波形生成モデルの学習（STFT SPECTRAL LOSS FOR TRAINING A NEURAL SPEECH WAVEFORM MODEL）</news:title>
   <news:publication_date>2026-06-28T22:00:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705978</loc>
  <lastmod>2026-06-28T22:00:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルソース・フィルタ波形モデルによる音声合成の高速化（NEURAL SOURCE-FILTER-BASED WAVEFORM MODEL FOR STATISTICAL PARAMETRIC SPEECH SYNTHESIS）</news:title>
   <news:publication_date>2026-06-28T22:00:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705976</loc>
  <lastmod>2026-06-28T21:59:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>裾適応fダイバージェンスを用いた変分推論（Variational Inference with Tail-adaptive f-Divergence）</news:title>
   <news:publication_date>2026-06-28T21:59:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705974</loc>
  <lastmod>2026-06-28T21:59:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-28T21:59:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705972</loc>
  <lastmod>2026-06-28T21:59:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705970</loc>
  <lastmod>2026-06-28T21:58:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-28T21:58:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-06-28T21:58:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-06-28T21:07:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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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:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的事例に対する一般化の理論的理解（Rademacher Complexity for Adversarially Robust Generalization）</news:title>
   <news:publication_date>2026-06-28T21:06:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705958</loc>
  <lastmod>2026-06-28T21:06:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト適応型生成対抗ネットワークによる自然言語での画像操作（Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language）</news:title>
   <news:publication_date>2026-06-28T21:06:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705956</loc>
  <lastmod>2026-06-28T21:06:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>システムログ処理の高速化と半教師あり学習（Accelerating System Log Processing by Semi-supervised Learning）</news:title>
   <news:publication_date>2026-06-28T21:06:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705954</loc>
  <lastmod>2026-06-28T21:05:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>保護栽培環境向けスイートペッパー収穫ロボット（A Sweet Pepper Harvesting Robot for Protected Cropping Environments）</news:title>
   <news:publication_date>2026-06-28T21:05:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705952</loc>
  <lastmod>2026-06-28T20:14:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層構造データの確率的クラスタリングと複合輸送距離（Probabilistic Multilevel Clustering via Composite Transportation Distance）</news:title>
   <news:publication_date>2026-06-28T20:14:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705950</loc>
  <lastmod>2026-06-28T20:14:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>忘れずに学ぶ学習法（Learning to Learn Without Forgetting by Maximizing Transfer and Minimizing Interference）</news:title>
   <news:publication_date>2026-06-28T20:14:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705948</loc>
  <lastmod>2026-06-28T20:13:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフニューラルネットワークの平均場理論による分割性能の解明（Mean-field theory of graph neural networks in graph partitioning）</news:title>
   <news:publication_date>2026-06-28T20:13:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705946</loc>
  <lastmod>2026-06-28T20:12:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースロジスティック回帰による離散対向グラフモデルの学習（Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models）</news:title>
   <news:publication_date>2026-06-28T20:12:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705944</loc>
  <lastmod>2026-06-28T20:12:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MMDネットワークによる半教師付き翻訳（Semi-Supervised Translation with MMD Networks）</news:title>
   <news:publication_date>2026-06-28T20:12:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705942</loc>
  <lastmod>2026-06-28T20:12:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模グラフを効率的に学習する仕組み（Accurate, Efficient and Scalable Graph Embedding）</news:title>
   <news:publication_date>2026-06-28T20:12:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705940</loc>
  <lastmod>2026-06-28T20:11:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散テンソル分解のスムーズ解析（Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons）</news:title>
   <news:publication_date>2026-06-28T20:11:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705938</loc>
  <lastmod>2026-06-28T19:21:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非並列テキスト転換の教師なし評価指標と学習基準（Unsupervised Evaluation Metrics and Learning Criteria for Non-Parallel Textual Transfer）</news:title>
   <news:publication_date>2026-06-28T19:21:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705936</loc>
  <lastmod>2026-06-28T19:20:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相関の強いGPポスターの効率的サンプリングを可能にするRMHMCの実装（An Efficient Implementation of Riemannian Manifold Hamiltonian Monte Carlo for Gaussian Process Models）</news:title>
   <news:publication_date>2026-06-28T19:20:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705934</loc>
  <lastmod>2026-06-28T19:20:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>材料シミュレーションのための均一に高精度な原子間ポテンシャルの能動学習（Active Learning of Uniformly Accurate Inter-atomic Potentials for Materials Simulation）</news:title>
   <news:publication_date>2026-06-28T19:20:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705932</loc>
  <lastmod>2026-06-28T19:19:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変化面──多次元的変化点と反事実予測（Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction）</news:title>
   <news:publication_date>2026-06-28T19:19:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705930</loc>
  <lastmod>2026-06-28T19:19:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胎児心エコー動画における局所時空間解剖学的位置特定（SEQUENTIAL ANATOMY LOCALIZATION IN FETAL ECHOCARDIOGRAPHY VIDEO）</news:title>
   <news:publication_date>2026-06-28T19:19:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705928</loc>
  <lastmod>2026-06-28T19:19:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コスト意識的因果グラフ学習の実験デザイン（Experimental Design for Cost-Aware Learning of Causal Graphs）</news:title>
   <news:publication_date>2026-06-28T19:19:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705926</loc>
  <lastmod>2026-06-28T19:19:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汚れた訓練データから学ぶ反復トリム損失最小化（Learning with Bad Training Data via Iterative Trimmed Loss Minimization）</news:title>
   <news:publication_date>2026-06-28T19:19:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705924</loc>
  <lastmod>2026-06-28T18:28:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>上位ρ分位からk本の腕を選ぶ探索手法の考察（Exploring k out of Top ρ Fraction of Arms in Stochastic Bandits）</news:title>
   <news:publication_date>2026-06-28T18:28:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705922</loc>
  <lastmod>2026-06-28T18:27:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙の夜明けにおける21cm信号の解析的定式化（Analytic Formulation of 21 cm Signal from Cosmic Dawn: Lyα Fluctuations）</news:title>
   <news:publication_date>2026-06-28T18:27:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705920</loc>
  <lastmod>2026-06-28T18:27:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LPCNetによる低コスト音声合成（LPCNet: IMPROVING NEURAL SPEECH SYNTHESIS THROUGH LINEAR PREDICTION）</news:title>
   <news:publication_date>2026-06-28T18:27:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705918</loc>
  <lastmod>2026-06-28T18:26:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>資源制約下で「最大値」を狙うオンライン学習フレームワーク（MaxHedge: Maximising a Maximum Online）</news:title>
   <news:publication_date>2026-06-28T18:26:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705916</loc>
  <lastmod>2026-06-28T18:26:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模視覚データを機械学習向けに高速に扱う仕組み（VDMS: Efficient Big-Visual-Data Access for Machine Learning Workloads）</news:title>
   <news:publication_date>2026-06-28T18:26:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705914</loc>
  <lastmod>2026-06-28T18:25:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像ノイズ除去のための強化畳み込みニューラルネットワーク（Enhanced CNN for image denoising）</news:title>
   <news:publication_date>2026-06-28T18:25:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705912</loc>
  <lastmod>2026-06-28T18:25:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>雲を「ノイズ」と見なす衛星画像の頑健なセグメンテーション（Convolutional LSTMs for Cloud-Robust Segmentation of Remote Sensing Imagery）</news:title>
   <news:publication_date>2026-06-28T18:25:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705910</loc>
  <lastmod>2026-06-28T17:34:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>専門家助言の統合による差別保持の問題（On preserving non-discrimination when combining expert advice）</news:title>
   <news:publication_date>2026-06-28T17:34:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705908</loc>
  <lastmod>2026-06-28T17:34:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパースペクトル動画における物体追跡の新手法（Object Tracking in Hyperspectral Videos with Convolutional Features and Kernelized Correlation Filter）</news:title>
   <news:publication_date>2026-06-28T17:34:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705906</loc>
  <lastmod>2026-06-28T17:34:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーグラフに基づく半教師あり学習アルゴリズムの音声認識への適用（Hypergraph Based Semi-Supervised Learning Algorithms Applied to Speech Recognition Problem）</news:title>
   <news:publication_date>2026-06-28T17:34:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705904</loc>
  <lastmod>2026-06-28T17:33:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>識別力を重視したチャネル削減（Discrimination-aware Channel Pruning for Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-28T17:33:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705902</loc>
  <lastmod>2026-06-28T17:33:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TV事前情報を用いた画像超解像の実用的意味（Image Super-Resolution Using TV Priori Guided Convolutional Network）</news:title>
   <news:publication_date>2026-06-28T17:33:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705900</loc>
  <lastmod>2026-06-28T17:33:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボットが「ノー」を学ぶ――否定語獲得における禁止と拒否のメカニズム（Robots Learning to Say ‘No’: Prohibition and Rejective Mechanisms in Acquisition of Linguistic Negation）</news:title>
   <news:publication_date>2026-06-28T17:33:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705898</loc>
  <lastmod>2026-06-28T17:32:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>四次元におけるボソン—フェルミオン双対性（Boson-fermion duality in four dimensions）</news:title>
   <news:publication_date>2026-06-28T17:32:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705896</loc>
  <lastmod>2026-06-28T16:41:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>陽子スピンの深い混合（Proton Spin in Deep Inelastic Scattering）</news:title>
   <news:publication_date>2026-06-28T16:41:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705894</loc>
  <lastmod>2026-06-28T16:41:33Z</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分散学習ガイド（A Hitchhiker’s Guide On Distributed Training of Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-28T16:41:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705892</loc>
  <lastmod>2026-06-28T16:41:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理世界で機能する音声の敵対的事例の生成（Robust Audio Adversarial Example for a Physical Attack）</news:title>
   <news:publication_date>2026-06-28T16:41:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705890</loc>
  <lastmod>2026-06-28T16:41:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰的ヤコビアン境界アルゴリズム RecurJac（RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications）</news:title>
   <news:publication_date>2026-06-28T16:41:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705888</loc>
  <lastmod>2026-06-28T16:40:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Affinity Network による複数物体追跡の再設計（Deep Affinity Network for Multiple Object Tracking）</news:title>
   <news:publication_date>2026-06-28T16:40:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705886</loc>
  <lastmod>2026-06-28T16:40:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パリティ奇数のニュートリノトルク検出（Parity-odd neutrino torque detection）</news:title>
   <news:publication_date>2026-06-28T16:40:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705884</loc>
  <lastmod>2026-06-28T16:40:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的系における安定で予測可能な構造の学習（Learning stable and predictive structures in kinetic systems: Benefits of a causal approach）</news:title>
   <news:publication_date>2026-06-28T16:40:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705882</loc>
  <lastmod>2026-06-28T15:49:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解析モデルと機械学習の融合による性能予測（Learning with Analytical Models）</news:title>
   <news:publication_date>2026-06-28T15:49:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705880</loc>
  <lastmod>2026-06-28T15:49:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シナプスから空間記憶地図へ（Through synapses to spatial memory maps: a topological model）</news:title>
   <news:publication_date>2026-06-28T15:49:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705878</loc>
  <lastmod>2026-06-28T15:48:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感度駆動型正則化によるスパースニューラルネット学習（Learning Sparse Neural Networks via Sensitivity-Driven Regularization）</news:title>
   <news:publication_date>2026-06-28T15:48:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705876</loc>
  <lastmod>2026-06-28T15:48:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模ネットワークの中心性を学習で高速化する研究（Computing Vertex Centrality Measures in Massive Real Networks with a Neural Learning Model）</news:title>
   <news:publication_date>2026-06-28T15:48:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705874</loc>
  <lastmod>2026-06-28T15:48:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習とリザバーコンピューティングによる分散型動的スペクトラムアクセス（Distributive Dynamic Spectrum Access through Deep Reinforcement Learning: A Reservoir Computing Based Approach）</news:title>
   <news:publication_date>2026-06-28T15:48:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705872</loc>
  <lastmod>2026-06-28T15:47:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観察されていないものを見る：並列化されたモンテカルロ木探索の単純なアプローチ（WATCH THE UNOBSERVED: A SIMPLE APPROACH TO PARALLELIZING MONTE CARLO TREE SEARCH）</news:title>
   <news:publication_date>2026-06-28T15:47:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705870</loc>
  <lastmod>2026-06-28T15:47:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク中心性指標における機械学習による近似手法（Machine Learning in Network Centrality Measures: Tutorial and Outlook）</news:title>
   <news:publication_date>2026-06-28T15:47:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705868</loc>
  <lastmod>2026-06-28T14:56:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルコフ連鎖の学習（On Learning Markov Chains）</news:title>
   <news:publication_date>2026-06-28T14:56:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705866</loc>
  <lastmod>2026-06-28T14:56:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習表現の理解に向けて：異なるニューラルネットワークはどの程度同じ表現を学ぶか (Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation)</news:title>
   <news:publication_date>2026-06-28T14:56:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705864</loc>
  <lastmod>2026-06-28T14:56:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DQN-TAMERによる人間-in-the-loop強化学習（DQN-TAMER: Human-in-the-Loop Reinforcement Learning with Intractable Feedback）</news:title>
   <news:publication_date>2026-06-28T14:56:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705862</loc>
  <lastmod>2026-06-28T14:55:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>残差ニューラルネットワークの深層極限（Deep Limits of Residual Neural Networks）</news:title>
   <news:publication_date>2026-06-28T14:55:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705860</loc>
  <lastmod>2026-06-28T14:54:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程事前分布付き変分オートエンコーダ（Gaussian Process Prior Variational Autoencoders）</news:title>
   <news:publication_date>2026-06-28T14:54:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705858</loc>
  <lastmod>2026-06-28T14:54:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形動力学のサンプル複雑度（Sample Complexity for Nonlinear Dynamics）</news:title>
   <news:publication_date>2026-06-28T14:54:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705856</loc>
  <lastmod>2026-06-28T14:54:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANに対する凸双対性フレームワークの示唆（A Convex Duality Framework for GANs）</news:title>
   <news:publication_date>2026-06-28T14:54:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705854</loc>
  <lastmod>2026-06-28T14:03:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>専用モジュールネットワークの類似性基準による訓練によるリアルタイム行動認識 (Real-time Action Recognition with Dissimilarity-based Training of Specialized Module Networks)</news:title>
   <news:publication_date>2026-06-28T14:03:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705852</loc>
  <lastmod>2026-06-28T14:02:58Z</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おけるクリティカルパスの蒸留（Distilling Critical Paths in Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-28T14:02:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705850</loc>
  <lastmod>2026-06-28T14:02:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共分散保存型敵対的拡張ネットワーク（Low-shot Learning via Covariance-Preserving Adversarial Augmentation Networks）</news:title>
   <news:publication_date>2026-06-28T14:02:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705848</loc>
  <lastmod>2026-06-28T14:01:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CoSTARによるブロック積みデータセットとワークスペース制約（The CoSTAR Block Stacking Dataset: Learning with Workspace Constraints）</news:title>
   <news:publication_date>2026-06-28T14:01:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705846</loc>
  <lastmod>2026-06-28T14:01:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FGSMの正則化効果とその一般化（Regularization Effect of Fast Gradient Sign Method and its Generalization）</news:title>
   <news:publication_date>2026-06-28T14:01:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705844</loc>
  <lastmod>2026-06-28T14:01:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>堅牢な深層ニューラルネットワークの探索（Towards Robust Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-28T14:01:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705842</loc>
  <lastmod>2026-06-28T14:01:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数グループNB‑IoTネットワークの協調深層強化学習による最適化（Cooperative Deep Reinforcement Learning for Multiple-Group NB-IoT Networks Optimization）</news:title>
   <news:publication_date>2026-06-28T14:01:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705840</loc>
  <lastmod>2026-06-28T13:10:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報欠損に基づく表現学習の新潮流：Variational Deficiency Bottleneck（The Variational Deficiency Bottleneck）</news:title>
   <news:publication_date>2026-06-28T13:10:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705838</loc>
  <lastmod>2026-06-28T13:01:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インテリジェント・ナノフォトニクス：ナノスケールで光学と人工知能を融合する研究（Intelligent Nanophotonics: Merging Photonics and Artificial Intelligence at the Nanoscale）</news:title>
   <news:publication_date>2026-06-28T13:01:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705836</loc>
  <lastmod>2026-06-28T13:00:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチエージェント共通知識強化学習（Multi-Agent Common Knowledge）</news:title>
   <news:publication_date>2026-06-28T13:00:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705834</loc>
  <lastmod>2026-06-28T13:00:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワイヤレスバックスキャッタで繰り返し動作を認識・計測する（From Communication to Sensing: Recognizing and Counting Repetitive Motions with Wireless Backscattering）</news:title>
   <news:publication_date>2026-06-28T13:00:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705832</loc>
  <lastmod>2026-06-28T13:00:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stein Variational Gradient Descentのモーメント一致性（Stein Variational Gradient Descent as Moment Matching）</news:title>
   <news:publication_date>2026-06-28T13:00:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705830</loc>
  <lastmod>2026-06-28T13:00:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実な入力を扱う回帰木（Uncertain Trees: Dealing with Uncertain Inputs in Regression Trees）</news:title>
   <news:publication_date>2026-06-28T13:00:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705828</loc>
  <lastmod>2026-06-28T12:59:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>主成分分析と深層ニューラルネットワークによる船体最適化（Hull Form Optimization with Principal Component Analysis and Deep Neural Network）</news:title>
   <news:publication_date>2026-06-28T12:59:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705826</loc>
  <lastmod>2026-06-28T12:08:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロブログを用いた疑わしいニュース検出（Suspicious News Detection Using Micro Blog Text）</news:title>
   <news:publication_date>2026-06-28T12:08:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705824</loc>
  <lastmod>2026-06-28T11:59:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートシティにおけるSDN・AI・ビッグデータの統合的活用（Towards Smart City Innovation Under the Perspective of Software-Defined Networking, Artificial Intelligence and Big Data）</news:title>
   <news:publication_date>2026-06-28T11:59:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705822</loc>
  <lastmod>2026-06-28T11:59:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒエラルキー型ソフトマックスのXMLCへの無後悔一般化（A no-regret generalization of hierarchical softmax to extreme multi-label classification）</news:title>
   <news:publication_date>2026-06-28T11:59:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705820</loc>
  <lastmod>2026-06-28T11:58:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハーディのパラドックスを用いた実用的なノーシグナリング証明ランダムネス増幅と実験実装 (Practical No-Signalling proof Randomness Amplification using Hardy paradoxes and its experimental implementation)</news:title>
   <news:publication_date>2026-06-28T11:58:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705818</loc>
  <lastmod>2026-06-28T11:58:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みネットワークとアダマールネットワークの等価性（On the Equivalence of Convolutional and Hadamard Networks using DFT）</news:title>
   <news:publication_date>2026-06-28T11:58:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705816</loc>
  <lastmod>2026-06-28T11:58:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラウザで協働設計するニューラルネットワーク編集ツール（Fabrik: An online collaborative neural network editor）</news:title>
   <news:publication_date>2026-06-28T11:58:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705814</loc>
  <lastmod>2026-06-28T11:58:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>活性化関数の自動選択手法によるハイブリッド深層ニューラルネットワーク設計（A Methodology for Automatic Selection of Activation Functions to Design Hybrid Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-28T11:58:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705812</loc>
  <lastmod>2026-06-28T11:06:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>区間タイプの特徴化に基づく時系列クラスタリング（Time series clustering based on the characterisation of segment typologies）</news:title>
   <news:publication_date>2026-06-28T11:06:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705810</loc>
  <lastmod>2026-06-28T10:58:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆方向（後方角度）でのω光生成過程における核子Reggeonとパートン寄与の役割（Features of ω photoproduction off proton target at backward angles : Role of nucleon Reggeon in u-channel with parton contributions）</news:title>
   <news:publication_date>2026-06-28T10:58:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705808</loc>
  <lastmod>2026-06-28T10:57:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実験データで観察データの隠れ交絡を是正する方法（Removing Hidden Confounding by Experimental Grounding）</news:title>
   <news:publication_date>2026-06-28T10:57:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705806</loc>
  <lastmod>2026-06-28T10:57:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RGBとDepthを横断する人物再識別のためのクロスモーダル蒸留（Cross-Modal Distillation for Person Re-Identification）</news:title>
   <news:publication_date>2026-06-28T10:57:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705804</loc>
  <lastmod>2026-06-28T10:57:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による雑音除去の実践と意義（Deep learning for denoising）</news:title>
   <news:publication_date>2026-06-28T10:57:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705802</loc>
  <lastmod>2026-06-28T10:56:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル比較のための判別的特徴抽出（Informative Features for Model Comparison）</news:title>
   <news:publication_date>2026-06-28T10:56:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705800</loc>
  <lastmod>2026-06-28T10:56:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集団知能のエージェントベースモデル入門（Agent-based models of collective intelligence）</news:title>
   <news:publication_date>2026-06-28T10:56:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705798</loc>
  <lastmod>2026-06-28T10:05:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡データを扱うマルチラベル分類の改善（Handling Imbalanced Dataset in Multi-label Text Categorization using Bagging and Adaptive Boosting）</news:title>
   <news:publication_date>2026-06-28T10:05:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705796</loc>
  <lastmod>2026-06-28T10:05:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTのための学習と管理：適応性とスケーラビリティへの挑戦（Learning and Management for Internet-of-Things: Accounting for Adaptivity and Scalability）</news:title>
   <news:publication_date>2026-06-28T10:05:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705794</loc>
  <lastmod>2026-06-28T10:05:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトゲート型Warping-GANによる姿勢誘導人物画像生成（Soft-Gated Warping-GAN for Pose-Guided Person Image Synthesis）</news:title>
   <news:publication_date>2026-06-28T10:05:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705792</loc>
  <lastmod>2026-06-28T10:04:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非局所フロッキング動力学：粒子シミュレーションからPDEの分数次数を学習する（Nonlocal flocking dynamics: Learning the fractional order of PDEs from particle simulations）</news:title>
   <news:publication_date>2026-06-28T10:04:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705790</loc>
  <lastmod>2026-06-28T10:04:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼できる予測確率の調整法の実務的進化（Attended Temperature Scaling: A Practical Approach for Calibrating Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-28T10:04:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705788</loc>
  <lastmod>2026-06-28T10:04:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>忘却に対抗する自己教師ありGAN（Self-Supervised GAN to Counter Forgetting）</news:title>
   <news:publication_date>2026-06-28T10:04:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705786</loc>
  <lastmod>2026-06-28T10:04:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>余クラス受容野を持つ畳み込みニューラルネットワーク（Convolutional neural networks with extra-classical receptive fields）</news:title>
   <news:publication_date>2026-06-28T10:04:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705784</loc>
  <lastmod>2026-06-28T09:13:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈性に基づく敵対サンプル検出（Attacks Meet Interpretability: Attribute-steered Detection of Adversarial Samples）</news:title>
   <news:publication_date>2026-06-28T09:13:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705782</loc>
  <lastmod>2026-06-28T09:12:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネルとレンジ空間に基づく勾配不要学習（Gradient-Free Learning Based on the Kernel and the Range Space）</news:title>
   <news:publication_date>2026-06-28T09:12:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705780</loc>
  <lastmod>2026-06-28T09:12:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習による抽象オプションの階層化（Learning Abstract Options）</news:title>
   <news:publication_date>2026-06-28T09:12:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705778</loc>
  <lastmod>2026-06-28T09:12:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長距離特徴伝播を効率化する二重注意機構（A2-Nets: Double Attention Networks）</news:title>
   <news:publication_date>2026-06-28T09:12:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705776</loc>
  <lastmod>2026-06-28T09:11:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短セグメント心音分類のための深層畳み込みニューラルネットワークアンサンブル（Short-segment heart sound classification using an ensemble of deep convolutional neural networks）</news:title>
   <news:publication_date>2026-06-28T09:11:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705774</loc>
  <lastmod>2026-06-28T09:11:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>滑らかな分布に対するkNN情報推定量の解析（Analysis of KNN Information Estimators for Smooth Distributions）</news:title>
   <news:publication_date>2026-06-28T09:11:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705772</loc>
  <lastmod>2026-06-28T09:11:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳腫瘍セグメンテーションの体積畳み込みニューラルネットワーク（A Volumetric Convolutional Neural Network for Brain Tumor Segmentation）</news:title>
   <news:publication_date>2026-06-28T09:11:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705770</loc>
  <lastmod>2026-06-28T08:20:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルセンサデータの匿名化（Mobile Sensor Data Anonymization）</news:title>
   <news:publication_date>2026-06-28T08:20:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705768</loc>
  <lastmod>2026-06-28T08:11:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>明示的・暗黙的コミュニケーションによる効率的で信頼できる社会的ナビゲーション（Efficient and Trustworthy Social Navigation Via Explicit and Implicit Robot-Human Communication）</news:title>
   <news:publication_date>2026-06-28T08:11:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705766</loc>
  <lastmod>2026-06-28T08:11:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床精神医学で解釈可能な推論を実現するMCAルールマイニング (MCA-based Rule Mining Enables Interpretable Inference in Clinical Psychiatry)</news:title>
   <news:publication_date>2026-06-28T08:11:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705764</loc>
  <lastmod>2026-06-28T08:10:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>気象とサウンドスケープの形状を監視する新しい統計手法（Monitoring the shape of weather, soundscapes, and dynamical systems: a new statistic for dimension-driven data analysis on large data sets）</news:title>
   <news:publication_date>2026-06-28T08:10:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705762</loc>
  <lastmod>2026-06-28T08:10:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般確率空間における多変量情報量の推定器（Estimators for Multivariate Information Measures in General Probability Spaces）</news:title>
   <news:publication_date>2026-06-28T08:10:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705760</loc>
  <lastmod>2026-06-28T08:10:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間のデモと介入を効率的に組み合わせた安全なリアルタイム学習（Efficiently Combining Human Demonstrations and Interventions for Safe Training of Autonomous Systems in Real-Time）</news:title>
   <news:publication_date>2026-06-28T08:10:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705758</loc>
  <lastmod>2026-06-28T08:10:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>監視映像の品質を自動判定する深層畳み込みネットワーク（DEEP CONVOLUTIONAL NEURAL NETWORK APPLIED TO QUALITY ASSESSMENT FOR VIDEO TRACKING）</news:title>
   <news:publication_date>2026-06-28T08:10:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705756</loc>
  <lastmod>2026-06-28T07:18:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトログラム・チャンネルU-Net：音源分離を直観的に解く（SPECTROGRAM-CHANNELS U-NET: A SOURCE SEPARATION MODEL）</news:title>
   <news:publication_date>2026-06-28T07:18:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705754</loc>
  <lastmod>2026-06-28T07:11:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>凸であっても不整合な代替損失関数の学習保証の定量化（Quantifying Learning Guarantees for Convex but Inconsistent Surrogates）</news:title>
   <news:publication_date>2026-06-28T07:11:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705752</loc>
  <lastmod>2026-06-28T07:11:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地震カタログに基づく機械学習による実験室断層状態の識別と完全度閾値の影響（Earthquake catalog-based machine learning identification of laboratory fault states and the effects of magnitude of completeness）</news:title>
   <news:publication_date>2026-06-28T07:11:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705750</loc>
  <lastmod>2026-06-28T07:10:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Attentionベース階層デコーダによるGUIからの自動コード生成（Automatic Graphics Program Generation using Attention-Based Hierarchical Decoder）</news:title>
   <news:publication_date>2026-06-28T07:10:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705748</loc>
  <lastmod>2026-06-28T07:10:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多重袋（bags-of-bags）で学ぶネットワーク設計の革新 — LEARNING AND INTERPRETING MULTI-MULTI-INSTANCE LEARNING NETWORKS (LEARNING AND INTERPRETING MULTI-MULTI-INSTANCE LEARNING NETWORKS)</news:title>
   <news:publication_date>2026-06-28T07:10:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705746</loc>
  <lastmod>2026-06-28T07:09:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Whetstoneによる二値通信ニューラルネットワーク訓練法（Whetstone: A Method for Training Deep Artificial Neural Networks for Binary Communication）</news:title>
   <news:publication_date>2026-06-28T07:09:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705744</loc>
  <lastmod>2026-06-28T07:09:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動微分の現在地と進むべき方向（Automatic differentiation in ML: Where we are and where we should be going）</news:title>
   <news:publication_date>2026-06-28T07:09:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705742</loc>
  <lastmod>2026-06-28T06:18:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相空間積分に対するニューラルネットワークアプローチ (Neural Network-Based Approach to Phase Space Integration)</news:title>
   <news:publication_date>2026-06-28T06:18:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705740</loc>
  <lastmod>2026-06-28T06:18:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NMBS-IIフィールドにおけるIRAC深層モザイク化の意義（IRAC mapping of the NMBS-II fields）</news:title>
   <news:publication_date>2026-06-28T06:18:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705738</loc>
  <lastmod>2026-06-28T06:17:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模経験的リスク最小化のための効率的分散ヘッセ非依存アルゴリズム（Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy）</news:title>
   <news:publication_date>2026-06-28T06:17:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705736</loc>
  <lastmod>2026-06-28T06:17:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定性保証付き強化学習：制御理論的視点での検証（STABILITY-CERTIFIED REINFORCEMENT LEARNING: A CONTROL-THEORETIC PERSPECTIVE）</news:title>
   <news:publication_date>2026-06-28T06:17:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705734</loc>
  <lastmod>2026-06-28T06:17:16Z</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から救援ニーズを自動抽出・順位付けする手法（Automatic Identification and Ranking of Emergency Aids in Social Media Macro Community）</news:title>
   <news:publication_date>2026-06-28T06:17:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705732</loc>
  <lastmod>2026-06-28T06:17:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散学習における情報ボトルネック法（Information Bottleneck Methods for Distributed Learning）</news:title>
   <news:publication_date>2026-06-28T06:17:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705730</loc>
  <lastmod>2026-06-28T06:16:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的パラメータの機械学習による推定（Machine learning determination of dynamical parameters: The Ising model case）</news:title>
   <news:publication_date>2026-06-28T06:16:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705728</loc>
  <lastmod>2026-06-28T05:25:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>次世代電波望遠鏡による系外惑星のトランジット観測（Exoplanet Transits with Next-Generation Radio Telescopes）</news:title>
   <news:publication_date>2026-06-28T05:25:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705726</loc>
  <lastmod>2026-06-28T05:25:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話し言葉の協調構造解析（Parsing Coordination for Spoken Language Understanding）</news:title>
   <news:publication_date>2026-06-28T05:25:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705724</loc>
  <lastmod>2026-06-28T05:25:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>比較ベースのサロゲートモデルと能動的共分散行列適応を用いた文脈付き方策探索の実証評価 (Empirical Evaluation of Contextual Policy Search with a Comparison-based Surrogate Model and Active Covariance Matrix Adaptation)</news:title>
   <news:publication_date>2026-06-28T05:25:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705722</loc>
  <lastmod>2026-06-28T05:24:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANを使ったスケーラブルなアンバランス最適輸送の実装戦略（SCALABLE UNBALANCED OPTIMAL TRANSPORT USING GENERATIVE ADVERSARIAL NETWORKS）</news:title>
   <news:publication_date>2026-06-28T05:24:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705720</loc>
  <lastmod>2026-06-28T05:24:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層反応性方策の転移によるMDP計画（Transfer of Deep Reactive Policies for MDP Planning）</news:title>
   <news:publication_date>2026-06-28T05:24:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705718</loc>
  <lastmod>2026-06-28T05:24:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生涯オンライン学習のための知識蓄積（Accumulating Knowledge for Lifelong Online Learning）</news:title>
   <news:publication_date>2026-06-28T05:24:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705716</loc>
  <lastmod>2026-06-28T05:23:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前処理不要の計算的組織染色と脱染の実現（Computational Histological Staining and Destaining of Prostate Core Biopsy RGB Images with Generative Adversarial Neural Networks）</news:title>
   <news:publication_date>2026-06-28T05:23:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705714</loc>
  <lastmod>2026-06-28T04:33:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TanDEM-XとCartosat-1の標高データ融合による都市域DEM精度向上（Fusion of TanDEM-X and Cartosat-1 Elevation Data Supported by Neural Network-Predicted Weight Maps）</news:title>
   <news:publication_date>2026-06-28T04:33:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705712</loc>
  <lastmod>2026-06-28T04:32:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VAEの事前分布を再サンプリングする手法（Resampled Priors for Variational Autoencoders）</news:title>
   <news:publication_date>2026-06-28T04:32:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705710</loc>
  <lastmod>2026-06-28T04:32:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子カルテの退院サマリーの抽出的要約（Extractive Summarization of Electronic Health Record Discharge Notes）</news:title>
   <news:publication_date>2026-06-28T04:32:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705708</loc>
  <lastmod>2026-06-28T04:32:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>樹状突起を用いた皮質マイクロ回路は逆伝播を近似する (Dendritic cortical microcircuits approximate the backpropagation algorithm)</news:title>
   <news:publication_date>2026-06-28T04:32:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705706</loc>
  <lastmod>2026-06-28T04:32:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚情報からの連続動作学習を効率化する深層内発的動機づけアクター・クリティック（Deep intrinsically motivated continuous actor-critic for efficient robotic visuomotor skill learning）</news:title>
   <news:publication_date>2026-06-28T04:32:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705704</loc>
  <lastmod>2026-06-28T04:32:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散型IoTシステムのための新興エッジコンピューティング技術（Emerging Edge Computing Technologies for Distributed Internet of Things (IoT) Systems）</news:title>
   <news:publication_date>2026-06-28T04:32:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705702</loc>
  <lastmod>2026-06-28T04:31:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル向け随時ステレオ画像深度推定（Anytime Stereo Image Depth Estimation on Mobile Devices）</news:title>
   <news:publication_date>2026-06-28T04:31:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705700</loc>
  <lastmod>2026-06-28T03:40:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノックオフ手法の安定化（Stabilizing Knockoffs: Multiple Simultaneous Knockoffs and Entropy Maximization）</news:title>
   <news:publication_date>2026-06-28T03:40:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705698</loc>
  <lastmod>2026-06-28T03:40:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>システムピークへの寄与に基づくデータ駆動型顧客セグメンテーション（A Data-Driven Customer Segmentation Strategy Based on Contribution to System Peak Demand）</news:title>
   <news:publication_date>2026-06-28T03:40:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705696</loc>
  <lastmod>2026-06-28T03:40:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPUで加速する室内インパルス応答シミュレーション用Pythonライブラリ（gpuRIR: A Python Library for Room Impulse Response Simulation with GPU Acceleration）</news:title>
   <news:publication_date>2026-06-28T03:40:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705694</loc>
  <lastmod>2026-06-28T03:39:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成モデルを用いた外れ値検出の理論と実装（Outlier Detection using Generative Models with Theoretical Performance Guarantees）</news:title>
   <news:publication_date>2026-06-28T03:39:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705692</loc>
  <lastmod>2026-06-28T03:39:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークによる分子の平衡構造生成（Generating equilibrium molecules with deep neural networks）</news:title>
   <news:publication_date>2026-06-28T03:39:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705690</loc>
  <lastmod>2026-06-28T03:39:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>過剰パラメータ化がEMにもたらす利点（Benefits of over-parameterization with EM）</news:title>
   <news:publication_date>2026-06-28T03:39:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705688</loc>
  <lastmod>2026-06-28T03:38:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピラミダルFSMNとラティスフリーMMIによる音声認識精度向上（A NOVEL PYRAMIDAL-FSMN ARCHITECTURE WITH LATTICE-FREE MMI FOR SPEECH RECOGNITION）</news:title>
   <news:publication_date>2026-06-28T03:38:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705686</loc>
  <lastmod>2026-06-28T02:47:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>見えない環境での音声強調を拡張するノイズ埋め込みと大規模環境学習（Scaling Speech Enhancement in Unseen Environments with Noise Embeddings）</news:title>
   <news:publication_date>2026-06-28T02:47:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705684</loc>
  <lastmod>2026-06-28T02:47:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バルカン地域のエネルギー消費予測における多層パーセプトロンと重回帰の比較（Comparing Multilayer Perceptron and Multiple Regression Models for Predicting Energy Use in the Balkans）</news:title>
   <news:publication_date>2026-06-28T02:47:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705682</loc>
  <lastmod>2026-06-28T02:47:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル端末で動くリアルタイム文脈学習とIoT制御（Real-time Context-aware Learning System for IoT Applications）</news:title>
   <news:publication_date>2026-06-28T02:47:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705680</loc>
  <lastmod>2026-06-28T02:46:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模銀河画像データベースのハイブリッド注釈手法（A hybrid approach to machine learning annotation of large galaxy image databases）</news:title>
   <news:publication_date>2026-06-28T02:46:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705678</loc>
  <lastmod>2026-06-28T02:46:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン学習における単一事例の複数回重み更新（Online learning using multiple times weight updating）</news:title>
   <news:publication_date>2026-06-28T02:46:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705676</loc>
  <lastmod>2026-06-28T02:46:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>聖書文脈でのドメイン適応：小規模データでの質問応答性能を高める手法（Finding Answers from the Word of God: Domain Adaptation for Neural Networks in Biblical Question Answering）</news:title>
   <news:publication_date>2026-06-28T02:46:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705674</loc>
  <lastmod>2026-06-28T01:55:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像における人物再識別を加速する空間・時間注意ネットワーク（Video-based Person Re-identification Using Spatial-Temporal Attention Networks）</news:title>
   <news:publication_date>2026-06-28T01:55:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705672</loc>
  <lastmod>2026-06-28T01:55:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スズの孤立電子対が招くキャリア捕獲の問題（Lone-pair effect on carrier capture in Cu2ZnSnS4 solar cells）</news:title>
   <news:publication_date>2026-06-28T01:55:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705670</loc>
  <lastmod>2026-06-28T01:54:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リーダーボードを超えて：InsightとDeploymentチャレンジの役割（Beyond the Leaderboard: Insight and Deployment Challenges to Address Research Problems）</news:title>
   <news:publication_date>2026-06-28T01:54:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705668</loc>
  <lastmod>2026-06-28T01:54:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミリ波V2XにおけるDeepRLベースの分散車両位置制御によるカバレッジ拡張（Deep-Reinforcement-Learning-Based Distributed Vehicle Position Controls for Coverage Expansion in mmWave V2X）</news:title>
   <news:publication_date>2026-06-28T01:54:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705666</loc>
  <lastmod>2026-06-28T01:54:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>直列結合同一DNNによる雑音型依存性の低減（CONCATENATED IDENTICAL DNN (CI-DNN) TO REDUCE NOISE-TYPE DEPENDENCE IN DNN-BASED SPEECH ENHANCEMENT）</news:title>
   <news:publication_date>2026-06-28T01:54:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705664</loc>
  <lastmod>2026-06-28T01:54:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CAPSULE-FORENSICSによる偽造画像・動画検出（CAPSULE-FORENSICS: USING CAPSULE NETWORKS TO DETECT FORGED IMAGES AND VIDEOS）</news:title>
   <news:publication_date>2026-06-28T01:54:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705662</loc>
  <lastmod>2026-06-28T01:54:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合モデルの大域収束をめざすCM-EMアルゴリズム（From the EM Algorithm to the CM-EM Algorithm for Global Convergence of Mixture Models）</news:title>
   <news:publication_date>2026-06-28T01:54:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705660</loc>
  <lastmod>2026-06-28T01:03:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HPC向けオンライン障害分類の実践（Online Fault Classification in HPC Systems through Machine Learning）</news:title>
   <news:publication_date>2026-06-28T01:03:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705658</loc>
  <lastmod>2026-06-28T01:03:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ポアソンガンマ動的システム（Deep Poisson gamma dynamical systems）</news:title>
   <news:publication_date>2026-06-28T01:03:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705656</loc>
  <lastmod>2026-06-28T01:03:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>4D OCTの最大強度投影に対する深層学習ベースの2.5Dフロー場推定（Deep learning based 2.5D flow field estimation for maximum intensity projections of 4D optical coherence tomography）</news:title>
   <news:publication_date>2026-06-28T01:03:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705654</loc>
  <lastmod>2026-06-28T01:02:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文章簡約のためのトランスフォーマとパラフレーズ規則の統合 (Integrating Transformer and Paraphrase Rules for Sentence Simplification)</news:title>
   <news:publication_date>2026-06-28T01:02:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705652</loc>
  <lastmod>2026-06-28T01:02:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CrystalGANで結晶構造を発見する（CrystalGAN: Learning to Discover Crystallographic Structures with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-28T01:02:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705650</loc>
  <lastmod>2026-06-28T01:02:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CubeSatにおける光通信の可能性（Optical Communication on CubeSats – Enabling the Next Era in Space Science –）</news:title>
   <news:publication_date>2026-06-28T01:02:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705648</loc>
  <lastmod>2026-06-28T01:01:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムフォレストの可逆（と非可逆）圧縮（Lossless (and Lossy) Compression of Random Forests）</news:title>
   <news:publication_date>2026-06-28T01:01:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705646</loc>
  <lastmod>2026-06-28T00:11:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特定相手を狙うマルチエージェント通信の設計（TarMAC: Targeted Multi-Agent Communication）</news:title>
   <news:publication_date>2026-06-28T00:11:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705644</loc>
  <lastmod>2026-06-28T00:11:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細粒度ビデオ分類における冗長性削減注意機構（Fine-grained Video Categorization with Redundancy Reduction Attention）</news:title>
   <news:publication_date>2026-06-28T00:11:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705642</loc>
  <lastmod>2026-06-28T00:10:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケールドデジタル学習環境におけるシーケンシャルなランダム化（Beyond A/B Testing: Sequential Randomization for Developing Interventions in Scaled Digital Learning Environments）</news:title>
   <news:publication_date>2026-06-28T00:10:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705640</loc>
  <lastmod>2026-06-28T00:10:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>住宅向けバッテリー最適運用における太陽光・負荷予測の活用（Using solar and load predictions in battery scheduling at the residential level）</news:title>
   <news:publication_date>2026-06-28T00:10:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705638</loc>
  <lastmod>2026-06-28T00:10:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>身体的問答のためのニューラル・モジュラー制御（Neural Modular Control for Embodied Question Answering）</news:title>
   <news:publication_date>2026-06-28T00:10:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705636</loc>
  <lastmod>2026-06-28T00:10:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>InversionNetによるフルウェーブフォーム反演の高速化と高精度化（InversionNet: A Real-Time and Accurate Full Waveform Inversion with CNNs and continuous CRFs）</news:title>
   <news:publication_date>2026-06-28T00:10:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705634</loc>
  <lastmod>2026-06-28T00:09:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース関係遷移モデルの学習（Learning Sparse Relational Transition Models）</news:title>
   <news:publication_date>2026-06-28T00:09:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705632</loc>
  <lastmod>2026-06-27T23:18:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散型マルチプレイヤーバンディットにおける通信不要の最適化（Game of Thrones: Fully Distributed Learning for Multi-Player Bandits）</news:title>
   <news:publication_date>2026-06-27T23:18:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705630</loc>
  <lastmod>2026-06-27T23:18:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔認識のデータ特化適応閾値（Data-specific Adaptive Threshold for Face Recognition and Authentication）</news:title>
   <news:publication_date>2026-06-27T23:18:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705628</loc>
  <lastmod>2026-06-27T23:18:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近傍表現を効率的に学習する Differentiable Boundary Sets（Efficient learning of neighbor representations for boundary trees and forests）</news:title>
   <news:publication_date>2026-06-27T23:18:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705626</loc>
  <lastmod>2026-06-27T23:17:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Size-Noise Tradeoffs in Generative Networks（Size-Noise Tradeoffs in Generative Networks）</news:title>
   <news:publication_date>2026-06-27T23:17:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705624</loc>
  <lastmod>2026-06-27T23:17:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンパスで学ぶ磁気共鳴の教育実験（Exploring magnetic resonance with a compass）</news:title>
   <news:publication_date>2026-06-27T23:17:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705622</loc>
  <lastmod>2026-06-27T23:17:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間を取り込むニューラルネットワーク—スティグメルジーを用いた時間表現（Using stigmergy to incorporate the time into artificial neural networks）</news:title>
   <news:publication_date>2026-06-27T23:17:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705620</loc>
  <lastmod>2026-06-27T23:17:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多人数並列化でマンフォールド最適化を効率化する手法（Communication Efficient Parallel Algorithms for Optimization on Manifolds）</news:title>
   <news:publication_date>2026-06-27T23:17:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705618</loc>
  <lastmod>2026-06-27T22:25:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トロイダルネマティクスにおけるユリ型ねじれ分布（Lily-like twist distribution in toroidal nematics）</news:title>
   <news:publication_date>2026-06-27T22:25:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705616</loc>
  <lastmod>2026-06-27T22:17:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散信頼を促進するブロックチェーン活用の試み（PROMOTING DISTRIBUTED TRUST IN MACHINE LEARNING AND COMPUTATIONAL SIMULATION VIA A BLOCKCHAIN NETWORK）</news:title>
   <news:publication_date>2026-06-27T22:17:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705614</loc>
  <lastmod>2026-06-27T22:16:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TensorFlowとCUDA対応MPIによる分散DNN学習のスケーラブル化（Scalable Distributed DNN Training using TensorFlow and CUDA-Aware MPI: Characterization, Designs, and Performance Evaluation）</news:title>
   <news:publication_date>2026-06-27T22:16:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705612</loc>
  <lastmod>2026-06-27T22:16:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>劣化文書の二値化を強化する敵対的ノイズ・テクスチャ増強（IMPROVING DOCUMENT BINARIZATION VIA ADVERSARIAL NOISE-TEXTURE AUGMENTATION）</news:title>
   <news:publication_date>2026-06-27T22:16:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705610</loc>
  <lastmod>2026-06-27T22:16:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回帰におけるアンサンブル損失関数による頑健化（RELF: Robust Regression Extended with Ensemble Loss Function）</news:title>
   <news:publication_date>2026-06-27T22:16:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705608</loc>
  <lastmod>2026-06-27T22:15:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一観測から学べるガウス埋め込み（Provable Gaussian Embedding with One Observation）</news:title>
   <news:publication_date>2026-06-27T22:15:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705606</loc>
  <lastmod>2026-06-27T22:15:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>放射線画像のテクスチャを高速に合成する技術（RADIOMIC SYNTHESIS USING DEEP CONVOLUTIONAL NEURAL NETWORKS）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705604</loc>
  <lastmod>2026-06-27T21:24:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低精度演算子の自動生成が切り開く現場適用の道（Automating Generation of Low Precision Deep Learning Operators）</news:title>
   <news:publication_date>2026-06-27T21:24:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705602</loc>
  <lastmod>2026-06-27T21:23:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配の一様収束と非凸学習の最適化（Uniform Convergence of Gradients for Non-Convex Learning and Optimization）</news:title>
   <news:publication_date>2026-06-27T21:23:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705600</loc>
  <lastmod>2026-06-27T21:23:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文法を教える敵対的分散（Teaching Syntax by Adversarial Distraction）</news:title>
   <news:publication_date>2026-06-27T21:23:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705598</loc>
  <lastmod>2026-06-27T21:22:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>退屈な宇宙論の「見えない差」を見分ける機械学習の力（On the dissection of degenerate cosmologies with machine learning）</news:title>
   <news:publication_date>2026-06-27T21:22:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705596</loc>
  <lastmod>2026-06-27T21:22:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複合視覚運動タスクのワンショット階層模倣学習（One-Shot Hierarchical Imitation Learning of Compound Visuomotor Tasks）</news:title>
   <news:publication_date>2026-06-27T21:22:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705594</loc>
  <lastmod>2026-06-27T21:22:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による異質な処置効果推定（Heterogeneous Treatment Effect Estimation through Deep Learning）</news:title>
   <news:publication_date>2026-06-27T21:22:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705592</loc>
  <lastmod>2026-06-27T21:21:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で標準宇宙論と修正重力モデルを見分ける（Distinguishing standard and modified gravity cosmologies with machine learning）</news:title>
   <news:publication_date>2026-06-27T21:21:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705590</loc>
  <lastmod>2026-06-27T20:30:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可逆的再帰型ニューラルネットワーク（Reversible Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-06-27T20:30:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705588</loc>
  <lastmod>2026-06-27T20:29:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチ正規化の効率化とサンプリング手法（Batch Normalization Sampling）</news:title>
   <news:publication_date>2026-06-27T20:29:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705586</loc>
  <lastmod>2026-06-27T20:28:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>力の位置不確実性下における最悪ケース構造解析の効率的サンプリング（EFFICIENT LOAD SAMPLING FOR WORST-CASE STRUCTURAL ANALYSIS UNDER FORCE LOCATION UNCERTAINTY）</news:title>
   <news:publication_date>2026-06-27T20:28:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705584</loc>
  <lastmod>2026-06-27T20:28:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>核ノルム正則化によるパネル回帰モデルの推定（Nuclear Norm Regularized Estimation of Panel Regression Models）</news:title>
   <news:publication_date>2026-06-27T20:28:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705582</loc>
  <lastmod>2026-06-27T20:28:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シグネチャモーメントによる確率過程の法則の特徴付け（Signature Moments to Characterize Laws of Stochastic Processes）</news:title>
   <news:publication_date>2026-06-27T20:28:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705580</loc>
  <lastmod>2026-06-27T20:27:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳表現のデコードとマルチモーダル学習（Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features）</news:title>
   <news:publication_date>2026-06-27T20:27:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705578</loc>
  <lastmod>2026-06-27T20:27:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的人口分布の高解像度生成（DeepDPM: Dynamic Population Mapping via Deep Neural Network）</news:title>
   <news:publication_date>2026-06-27T20:27:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705576</loc>
  <lastmod>2026-06-27T19:36:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソルに対するクロネッカー構造部分空間の一致検出（Tensor Matched Kronecker-Structured Subspace Detection for Missing Information）</news:title>
   <news:publication_date>2026-06-27T19:36:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705574</loc>
  <lastmod>2026-06-27T19:36:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間行動認識のハイパーパラメータ最適化に関する予備研究（A Preliminary Study on Hyperparameter Configuration for Human Activity Recognition）</news:title>
   <news:publication_date>2026-06-27T19:36:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705572</loc>
  <lastmod>2026-06-27T19:35:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分可変速度制限を深層強化学習で制御する研究（Differential Variable Speed Limits Control for Freeway Recurrent Bottlenecks via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-27T19:35:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705570</loc>
  <lastmod>2026-06-27T19:35:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アルツハイマー病の認知評価に関するVRとチューリング試験の応用（Cognitive Evaluation for the Diagnosis of Alzheimer’s Disease based on Turing Test and Virtual Environments）</news:title>
   <news:publication_date>2026-06-27T19:35:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705568</loc>
  <lastmod>2026-06-27T19:35:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン消費者レビューにおける両面（ツーサイド）議論の役割（Understanding the Role of Two-Sided Argumentation in Online Consumer Reviews: A Language-Based Perspective）</news:title>
   <news:publication_date>2026-06-27T19:35:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705566</loc>
  <lastmod>2026-06-27T19:35:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ないデータでも動く深層学習の現実（Learning Emotion from 100 Observations: Unexpected Robustness of Deep Learning under Strong Data Limitations）</news:title>
   <news:publication_date>2026-06-27T19:35:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705564</loc>
  <lastmod>2026-06-27T19:34:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>T-GANによる生成モデル訓練の新潮流（Training Generative Adversarial Networks Via Turing Test）</news:title>
   <news:publication_date>2026-06-27T19:34:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705562</loc>
  <lastmod>2026-06-27T18:43:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子チャネル学習と近似状態識別の効率的アルゴリズム（Sample Efficient Algorithms for Learning Quantum Channels in PAC Model and the Approximate State Discrimination Problem）</news:title>
   <news:publication_date>2026-06-27T18:43:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705560</loc>
  <lastmod>2026-06-27T18:43:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散領域における分類器回避の最小コスト保証（Evading Classifiers in Discrete Domains with Provable Optimality Guarantees）</news:title>
   <news:publication_date>2026-06-27T18:43:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705558</loc>
  <lastmod>2026-06-27T18:42:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HAR-Net: 深層表現と手作り特徴量を融合した人間行動認識（HAR-Net: Fusing Deep Representation and Hand-crafted Features for Human Activity Recognition）</news:title>
   <news:publication_date>2026-06-27T18:42:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705556</loc>
  <lastmod>2026-06-27T18:41:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語処理のためのベイズ圧縮（Bayesian Compression for Natural Language Processing）</news:title>
   <news:publication_date>2026-06-27T18:41:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705554</loc>
  <lastmod>2026-06-27T18:41:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い共分散轨道に基づく顔表情の自動解析（Automatic Analysis of Facial Expressions Based on Deep Covariance Trajectories）</news:title>
   <news:publication_date>2026-06-27T18:41:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705552</loc>
  <lastmod>2026-06-27T18:41:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡データに対するスーパーアンサンブル分類器（Superensemble Classifier for Improving Predictions in Imbalanced Datasets）</news:title>
   <news:publication_date>2026-06-27T18:41:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705550</loc>
  <lastmod>2026-06-27T18:41:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一の深度画像からの敵対的セマンティックシーン補完（Adversarial Semantic Scene Completion from a Single Depth Image）</news:title>
   <news:publication_date>2026-06-27T18:41:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705548</loc>
  <lastmod>2026-06-27T17:49:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>藻類の自動分類に関する研究（Investigating the Automatic Classification of Algae Using Fusion of Spectral and Morphological Characteristics of Algae via Deep Residual Learning）</news:title>
   <news:publication_date>2026-06-27T17:49:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705546</loc>
  <lastmod>2026-06-27T17:49:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重い裾の確率的線形バンディットに対するほぼ最適アルゴリズム（Almost Optimal Algorithms for Linear Stochastic Bandits with Heavy-Tailed Payoffs）</news:title>
   <news:publication_date>2026-06-27T17:49:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705544</loc>
  <lastmod>2026-06-27T17:49:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波形信号のエントロピーと圧縮に関する全館エネルギーデータの研究（Waveform Signal Entropy and Compression Study of Whole-Building Energy Datasets）</news:title>
   <news:publication_date>2026-06-27T17:49:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705542</loc>
  <lastmod>2026-06-27T17:48:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カウントデータの無向グラフィカルモデルの構造学習（Structure learning of undirected graphical models for count data）</news:title>
   <news:publication_date>2026-06-27T17:48:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705540</loc>
  <lastmod>2026-06-27T17:48:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短い発話に対する話者認証の補償（Short utterance compensation in speaker verification via cosine-based teacher-student learning of speaker embeddings）</news:title>
   <news:publication_date>2026-06-27T17:48:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705538</loc>
  <lastmod>2026-06-27T17:48:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロサービス、継続的アーキテクチャと技術的負債利息（Microservices, Continuous Architecture, and Technical Debt Interest: An Empirical Study）</news:title>
   <news:publication_date>2026-06-27T17:48:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705536</loc>
  <lastmod>2026-06-27T17:48:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANによるデータ拡張（GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-27T17:48:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-06-27T16:56:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異常から正常への翻訳による医用画像合成と病変検出（An Adversarial Learning Approach to Medical Image Synthesis for Lesion Detection）</news:title>
   <news:publication_date>2026-06-27T16:56:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-06-27T16:56:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>株価のジャンプ到来予測と新しい注意機構付きネットワーク（Forecasting of Jump Arrivals in Stock Prices: New Attention-based Network Architecture using Limit Order Book Data）</news:title>
   <news:publication_date>2026-06-27T16:56:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-06-27T16:55:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>格子緩和が相転移へ与える影響：機械学習ポテンシャルによる高エントロピー合金の研究 (Impact of lattice relaxations on phase transitions in a high-entropy alloy studied by machine-learning potentials)</news:title>
   <news:publication_date>2026-06-27T16:55:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/705528</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンパクトな語義セグメンテーションモデルの高速NAS（Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells）</news:title>
   <news:publication_date>2026-06-27T16:54:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/705526</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイキング神経回路で実現する適応的運動制御と学習（Adaptive motor control and learning in a spiking neural network realised on a mixed-signal neuromorphic processor）</news:title>
   <news:publication_date>2026-06-27T16:54:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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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・シーケンス変換における潜在分節とオンライン生成（Neural Sequence Transduction with Latent Segmentation）</news:title>
   <news:publication_date>2026-06-27T16:54:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変化する環境下で最適なオンライン学習を実現する手法（Adaptive Online Learning in Dynamic Environments）</news:title>
   <news:publication_date>2026-06-27T16:54:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/705520</loc>
  <lastmod>2026-06-27T16:02:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワークをガウス過程の視点で見る（A Gaussian Process perspective on Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-27T16:02:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/705518</loc>
  <lastmod>2026-06-27T16:01:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フラッシュX線単一粒子回折イメージングの教師あり分類手法（SUPERVISED CLASSIFICATION METHODS FOR FLASH X-RAY SINGLE PARTICLE DIFFRACTION IMAGING）</news:title>
   <news:publication_date>2026-06-27T16:01:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/705516</loc>
  <lastmod>2026-06-27T16:01:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知覚に基づく視覚対話型学習の再設計（Perceptual Visual Interactive Learning）</news:title>
   <news:publication_date>2026-06-27T16:01:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/705514</loc>
  <lastmod>2026-06-27T16:01:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的に頑健なガウス過程最適化（Adversarially Robust Optimization with Gaussian Processes）</news:title>
   <news:publication_date>2026-06-27T16:01:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/705512</loc>
  <lastmod>2026-06-27T16:01:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語が数学の学びを変える（The Role of Language in Teaching and Learning Mathematics）</news:title>
   <news:publication_date>2026-06-27T16:01:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/705510</loc>
  <lastmod>2026-06-27T16:00:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共分散推定によるRBMの効率的学習（EFFICIENT LEARNING OF RESTRICTED BOLTZMANN MACHINES USING COVARIANCE ESTIMATES）</news:title>
   <news:publication_date>2026-06-27T16:00:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/705508</loc>
  <lastmod>2026-06-27T16:00:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-27T16:00:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/705506</loc>
  <lastmod>2026-06-27T15:08:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-27T15:08:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/705504</loc>
  <lastmod>2026-06-27T15:01:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>法と敵対的機械学習（Law and Adversarial Machine Learning）</news:title>
   <news:publication_date>2026-06-27T15:01:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705502</loc>
  <lastmod>2026-06-27T15:01:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>偽ノード攻撃が明かすGCNの脆弱性（Fake Node Attacks on Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-06-27T15:01:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705500</loc>
  <lastmod>2026-06-27T15:00:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Word Embedding based Edit Distance（Word Embedding based Edit Distance）</news:title>
   <news:publication_date>2026-06-27T15:00:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
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