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   <news:title>LHC解析特化データセットをGANで生成する可能性（LHC analysis-specific datasets with Generative Adversarial Networks）</news:title>
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   <news:title>モノレイヤWSe2の点欠陥を第一原理で読む（First Principles Study of Intrinsic and Extrinsic Point Defects in Monolayer WSe2）</news:title>
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   <news:title>教育現場でのair:bitによる電子工作とプログラミング教育（Teaching Electronics and Programming in Norwegian Schools Using the air:bit Sensor Kit）</news:title>
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   <news:title>ローソク足を画像化して識別する手法（ENCODING CANDLESTICKS AS IMAGES FOR PATTERN CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORKS）</news:title>
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   <news:title>GridSimによる自律走行学習の実践的基盤（GridSim: A Vehicle Kinematics Engine for Deep Neuroevolutionary Control in Autonomous Driving）</news:title>
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   <news:title>ブラックホールは宇宙の発電機である（Black Holes as Cosmic Dynamos）</news:title>
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   <news:title>射影幾何代数によるユークリッド幾何の再構成（Projective geometric algebra: A new framework for doing euclidean geometry）</news:title>
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   <news:title>ゲーム離脱（チurn）予測で勝利した手法の解説（The Winning Solution to the IEEE CIG 2017 Game Data Mining Competition）</news:title>
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   <news:title>射影リード・ソロモン符号の深い穴の分類（Deep Holes of Projective Reed-Solomon Codes）</news:title>
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   <news:title>遺伝的アルゴリズムを用いたEEG特徴選択によるBCI分類精度向上（A GA-based feature selection of the EEG signals by classification evaluation: Application in BCI systems）</news:title>
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    <news:language>ja</news:language>
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   <news:title>数学教員養成におけるCoCalcの活用（USING COCALC AS A TRAINING TOOL FOR MATHEMATICS TEACHERS’ PRE-SERVICE TRAINING）</news:title>
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  <news:news>
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    <news:language>ja</news:language>
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   <news:title>QSMIを用いた深層教師付きハッシュによるコンテンツベース画像検索（Deep Supervised Hashing leveraging Quadratic Spherical Mutual Information for Content-based Image Retrieval）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>分散環境で勾配ノルムを直接最適化するDINGO（DINGO: Distributed Newton-Type Method for Gradient-Norm Optimization）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-26T21:23:21Z</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>記憶強化型生成モデルによるテニスの次ショット予測（Memory Augmented Deep Generative models for Forecasting the Next Shot Location in Tennis）</news:title>
   <news:publication_date>2026-07-26T21:23:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-26T21:23:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>大規模地球系モデルの効率的代替構築法（Efficient surrogate modeling methods for large-scale Earth system models based on machine learning techniques）</news:title>
   <news:publication_date>2026-07-26T21:23:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-26T21:22:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>インバータ系のリアルタイム安定化におけるcGAN活用（Generative Adversarial Networks for Real-time Stability of Inverter-based Systems）</news:title>
   <news:publication_date>2026-07-26T21:22:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-26T21:21:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>学生の行動的エンゲージメント検出の非侵襲・マルチモーダル手法（Unobtrusive and Multimodal Approach for Behavioral Engagement Detection of Students）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>行動はパスワードより雄弁である（Actions Speak Louder Than (Pass)words: Passive Authentication of Smartphone Users via Deep Temporal Features）</news:title>
   <news:publication_date>2026-07-26T21:21:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-26T21:21:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>可変長文字レベルRNNによるリード成約予測（Variable-sized input, character-level recurrent neural networks in lead generation: predicting close rates from raw user inputs）</news:title>
   <news:publication_date>2026-07-26T21:21:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-26T20:30:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepSDFによる連続形状表現の学習（DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation）</news:title>
   <news:publication_date>2026-07-26T20:30:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716269</loc>
  <lastmod>2026-07-26T20:29:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交差点における不確実性を考慮した運転者軌跡予測（Uncertainty-Aware Driver Trajectory Prediction at Urban Intersections）</news:title>
   <news:publication_date>2026-07-26T20:29:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716267</loc>
  <lastmod>2026-07-26T20:29:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の連続評価から学ぶ自動運転学習（RENEG AND BACKSEAT DRIVER: LEARNING FROM DEMONSTRATION WITH CONTINUOUS HUMAN FEEDBACK）</news:title>
   <news:publication_date>2026-07-26T20:29:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716265</loc>
  <lastmod>2026-07-26T20:28:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二部グラフの頂点表現学習が変える推薦と検索の精度（Learning Vertex Representations for Bipartite Networks）</news:title>
   <news:publication_date>2026-07-26T20:28:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716263</loc>
  <lastmod>2026-07-26T20:28:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レイリー波分散曲線と拡散場HVSRの共同解析によるサイト特性評価（Joint analysis of Rayleigh-wave dispersion curves and diffuse-field HVSR for site characterization）</news:title>
   <news:publication_date>2026-07-26T20:28:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716261</loc>
  <lastmod>2026-07-26T20:28:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敗血症性ショック児への血管作動薬反応を個別予測する研究（Predicting Individual Responses to Vasoactive Medications in Children with Septic Shock）</news:title>
   <news:publication_date>2026-07-26T20:28:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716259</loc>
  <lastmod>2026-07-26T20:27:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速なディープラーニングによる自動変調識別（Fast Deep Learning for Automatic Modulation Classification）</news:title>
   <news:publication_date>2026-07-26T20:27:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716257</loc>
  <lastmod>2026-07-26T19:35:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オートエンコーダによる逆問題解法（Solving inverse problems via auto-encoders）</news:title>
   <news:publication_date>2026-07-26T19:35:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716255</loc>
  <lastmod>2026-07-26T19:35:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非パラメトリックで超効率な平均処置効果推定量（A nonparametric super-efficient estimator of the average treatment effect）</news:title>
   <news:publication_date>2026-07-26T19:35:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716253</loc>
  <lastmod>2026-07-26T19:35:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音楽の音源分離におけるスペクトログラム特徴損失（Spectrogram Feature Losses for Music Source Separation）</news:title>
   <news:publication_date>2026-07-26T19:35:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716251</loc>
  <lastmod>2026-07-26T19:34:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ上のℓpベース半教師あり学習の理論と応用（ANALYSIS AND ALGORITHMS FOR ℓp-BASED SEMI-SUPERVISED LEARNING ON GRAPHS）</news:title>
   <news:publication_date>2026-07-26T19:34:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716249</loc>
  <lastmod>2026-07-26T19:34:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイジアン・プロフェット：オンライン意思決定の低後悔フレームワーク（The Bayesian Prophet: A Low-Regret Framework for Online Decision Making）</news:title>
   <news:publication_date>2026-07-26T19:34:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716247</loc>
  <lastmod>2026-07-26T19:34:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低フラックス状態の観測が示す核物理の示唆（A Low-Flux State in IRAS 00521–7054 seen with NuSTAR and XMM-Newton: Relativistic Reflection and an Ultrafast Outflow）</news:title>
   <news:publication_date>2026-07-26T19:34:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716245</loc>
  <lastmod>2026-07-26T19:34:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遺伝子発現から成長率を予測する手法（Predicting Growth Rate from Gene Expression）</news:title>
   <news:publication_date>2026-07-26T19:34:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716243</loc>
  <lastmod>2026-07-26T18:42:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベルバイアスの検出と修正（Identifying and Correcting Label Bias in Machine Learning）</news:title>
   <news:publication_date>2026-07-26T18:42:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716241</loc>
  <lastmod>2026-07-26T18:42:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現型赤方偏移と自己組織化写像による系統的赤shift推定（Phenotypic redshifts with self-organizing maps）</news:title>
   <news:publication_date>2026-07-26T18:42:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716239</loc>
  <lastmod>2026-07-26T18:42:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カスケードデコーダー：生物医療画像分割の汎用的デコーディング手法（CASCADE DECODER: A UNIVERSAL DECODING METHOD FOR BIOMEDICAL IMAGE SEGMENTATION）</news:title>
   <news:publication_date>2026-07-26T18:42:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716237</loc>
  <lastmod>2026-07-26T18:41:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低メモリ・小モデルで実用的なサリエンシー検出（Light-weighted Saliency Detection with Distinctively Lower Memory Cost and Model Size）</news:title>
   <news:publication_date>2026-07-26T18:41:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716235</loc>
  <lastmod>2026-07-26T18:40:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次的に読む質問応答モデルが示す実務的示唆（Incremental Reading for Question Answering）</news:title>
   <news:publication_date>2026-07-26T18:40:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716233</loc>
  <lastmod>2026-07-26T18:40:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポリ(イオン液体)を用いたCO2捕集と触媒応用（Poly(ionic liquid)s: platform for CO2 capture and catalysis）</news:title>
   <news:publication_date>2026-07-26T18:40:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716231</loc>
  <lastmod>2026-07-26T18:40:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>楕円体ハムの表面積・体積をカメラで推定する（Automatic Surface Area and Volume Prediction on Ellipsoidal Ham using Deep Learning）</news:title>
   <news:publication_date>2026-07-26T18:40:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716229</loc>
  <lastmod>2026-07-26T17:48:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Fusion：注意機構で導く因子化二次結合による音声・映像の感情認識（Deep Fusion: An Attention Guided Factorized Bilinear Pooling for Audio-video Emotion Recognition）</news:title>
   <news:publication_date>2026-07-26T17:48:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716227</loc>
  <lastmod>2026-07-26T17:48:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公正性制約を持つ組合せスリーピングバンディット（Combinatorial Sleeping Bandits with Fairness Constraints）</news:title>
   <news:publication_date>2026-07-26T17:48:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716225</loc>
  <lastmod>2026-07-26T17:48:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラウン運動の楽観的最適化（Optimistic Optimization of a Brownian）</news:title>
   <news:publication_date>2026-07-26T17:48:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716223</loc>
  <lastmod>2026-07-26T17:47:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空の動画を用いた太陽放射照度予測のディープラーニングアプローチ（A deep learning approach to solar-irradiance forecasting in sky-videos）</news:title>
   <news:publication_date>2026-07-26T17:47:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716221</loc>
  <lastmod>2026-07-26T17:47:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人工ボディ知覚のためのセンサーモーター学習（Sensorimotor learning for artificial body perception）</news:title>
   <news:publication_date>2026-07-26T17:47:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716219</loc>
  <lastmod>2026-07-26T17:47:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リスク志向マルコフゲームにおけるモデル化と強化学習（Model and Reinforcement Learning for Markov Games with Risk Preferences）</news:title>
   <news:publication_date>2026-07-26T17:47:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716217</loc>
  <lastmod>2026-07-26T17:47:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的・多忠実度に対応する深層サロゲートモデル（Conditional deep surrogate models for stochastic, high-dimensional, and multi-fidelity systems）</news:title>
   <news:publication_date>2026-07-26T17:47:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716215</loc>
  <lastmod>2026-07-26T16:56:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成T2-FLAIR造影の物理志向深層学習（Build-A-FLAIR: Synthetic T2-FLAIR Contrast Generation through Physics Informed Deep Learning）</news:title>
   <news:publication_date>2026-07-26T16:56:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716213</loc>
  <lastmod>2026-07-26T16:55:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Feature Boosting Network For 3D Pose Estimation（Feature Boosting Network For 3D Pose Estimation）</news:title>
   <news:publication_date>2026-07-26T16:55:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716211</loc>
  <lastmod>2026-07-26T16:55:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在変数を用いた実用的な可逆圧縮手法：Bits Back with ANS（PRACTICAL LOSSLESS COMPRESSION WITH LATENT VARIABLES USING BITS BACK CODING）</news:title>
   <news:publication_date>2026-07-26T16:55:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716209</loc>
  <lastmod>2026-07-26T16:54:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートビル換気サブシステムのデータ駆動モデリング（Data-driven Modelling of Smart Building Ventilation Subsystem）</news:title>
   <news:publication_date>2026-07-26T16:54:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716207</loc>
  <lastmod>2026-07-26T16:54:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形不等式制約とノイズを含む観測下でのガウス過程エミュレータの近似（APPROXIMATING GAUSSIAN PROCESS EMULATORS WITH LINEAR INEQUALITY CONSTRAINTS AND NOISY OBSERVATIONS VIA MC AND MCMC）</news:title>
   <news:publication_date>2026-07-26T16:54:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716205</loc>
  <lastmod>2026-07-26T16:54:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同期化された歌詞とボーカル特徴を用いた音楽感情検出（Exploiting Synchronized Lyrics and Vocal Features for Music Emotion Detection）</news:title>
   <news:publication_date>2026-07-26T16:54:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716203</loc>
  <lastmod>2026-07-26T16:53:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高分解能スペクトル（ハイパースペクトル）を用いた土壌質感の1次元畳み込みニューラルネットワークによる分類（SOIL TEXTURE CLASSIFICATION WITH 1D CONVOLUTIONAL NEURAL NETWORKS BASED ON HYPERSPECTRAL DATA）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716201</loc>
  <lastmod>2026-07-26T16:02:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習と連続体仮説（Machine learning and the Continuum Hypothesis）</news:title>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/716199</loc>
  <lastmod>2026-07-26T15:58:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム光学媒体の伝送行列を学習する（Learning Direct and Inverse Transmission Matrices）</news:title>
   <news:publication_date>2026-07-26T15:58:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716197</loc>
  <lastmod>2026-07-26T15:58:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mixed Variational Inference（Mixed Variational Inference）</news:title>
   <news:publication_date>2026-07-26T15:58:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716195</loc>
  <lastmod>2026-07-26T15:57:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ツイートの固有表現とスタンス注釈付きデータセット（A Tweet Dataset Annotated for Named Entity Recognition and Stance Detection）</news:title>
   <news:publication_date>2026-07-26T15:57:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716193</loc>
  <lastmod>2026-07-26T15:57:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>模倣正則化によるオフライン学習の安定化（Imitation-Regularized Offline Learning）</news:title>
   <news:publication_date>2026-07-26T15:57:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716191</loc>
  <lastmod>2026-07-26T15:56:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚を用いた自律探索と地図生成の学習（Learning Autonomous Exploration and Mapping with Semantic Vision）</news:title>
   <news:publication_date>2026-07-26T15:56:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716189</loc>
  <lastmod>2026-07-26T15:56:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公平かつ偏りのないアルゴリズム意思決定（Fair and Unbiased Algorithmic Decision Making）</news:title>
   <news:publication_date>2026-07-26T15:56:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716187</loc>
  <lastmod>2026-07-26T15:04:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グローバルからローカルへのメモリーポインターネットワーク（GLOBAL-TO-LOCAL MEMORY POINTER NETWORKS FOR TASK-ORIENTED DIALOGUE）</news:title>
   <news:publication_date>2026-07-26T15:04:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716185</loc>
  <lastmod>2026-07-26T15:04:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MAD-GANによる多変量時系列の異常検知（MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-07-26T15:04:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716183</loc>
  <lastmod>2026-07-26T15:03:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepCFによる協調フィルタリング再考（DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System）</news:title>
   <news:publication_date>2026-07-26T15:03:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716181</loc>
  <lastmod>2026-07-26T15:03:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>URNet：ユーザーが動的に縮小可能な残差ネットワーク（User-Resizable Residual Networks with Conditional Gating Module）</news:title>
   <news:publication_date>2026-07-26T15:03:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716179</loc>
  <lastmod>2026-07-26T15:03:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートビルにおける省エネと快適性の両立（Energy-Efficient Thermal Comfort Control in Smart Buildings via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-26T15:03:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716177</loc>
  <lastmod>2026-07-26T15:02:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>直交埋め込みに基づく深層クラスタリングによる単一チャネル音声分離（ORTHONORMAL EMBEDDING-BASED DEEP CLUSTERING FOR SINGLE-CHANNEL SPEECH SEPARATION）</news:title>
   <news:publication_date>2026-07-26T15:02:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716175</loc>
  <lastmod>2026-07-26T15:02:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アルイムネットによるダスタガ音楽生成と実務的示唆（Classical Music Generation in Distinct Dastgahs with AlimNet ACGAN）</news:title>
   <news:publication_date>2026-07-26T15:02:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716173</loc>
  <lastmod>2026-07-26T14:11:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>急変する動的環境下におけるパラメータ推定（Parameter Estimation in Abruptly Changing Dynamic Environments）</news:title>
   <news:publication_date>2026-07-26T14:11:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716171</loc>
  <lastmod>2026-07-26T14:05:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的訓練の限界とブラインドスポット攻撃（THE LIMITATIONS OF ADVERSARIAL TRAINING AND THE BLIND-SPOT ATTACK）</news:title>
   <news:publication_date>2026-07-26T14:05:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716169</loc>
  <lastmod>2026-07-26T14:05:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像合成とスタイル転送の分解と実務的示唆（Image Synthesis and Style Transfer）</news:title>
   <news:publication_date>2026-07-26T14:05:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716167</loc>
  <lastmod>2026-07-26T14:04:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的に変化するデータストリームにおける分位点追跡（Quantile Tracking in Dynamically Varying Data Streams Using a Generalized Exponentially Weighted Average of Observations）</news:title>
   <news:publication_date>2026-07-26T14:04:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716165</loc>
  <lastmod>2026-07-26T14:03:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なしセンサー選択のオンラインアルゴリズム (Online Algorithm for Unsupervised Sensor Selection)</news:title>
   <news:publication_date>2026-07-26T14:03:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716163</loc>
  <lastmod>2026-07-26T14:03:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>授業中の行動的エンゲージメント検出（Detecting Behavioral Engagement of Students in the Wild Based on Contextual and Visual Data）</news:title>
   <news:publication_date>2026-07-26T14:03:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716161</loc>
  <lastmod>2026-07-26T14:02:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PDF文書から類似表を統合・検索する深層学習手法（Integrating and querying similar tables from PDF documents using deep learning）</news:title>
   <news:publication_date>2026-07-26T14:02:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716159</loc>
  <lastmod>2026-07-26T13:10:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LDGM符号を用いた分散確率的勾配降下法の提案（Distributed Stochastic Gradient Descent Using LDGM Codes）</news:title>
   <news:publication_date>2026-07-26T13:10:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716157</loc>
  <lastmod>2026-07-26T13:10:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層とカーネルに基づく強化学習を組み合わせた敗血症治療戦略の改善（Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-26T13:10:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716155</loc>
  <lastmod>2026-07-26T13:10:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>配列ベースの深層学習モデル比較によるタンパク質相互作用予測（Comparing two deep learning sequence-based models for protein-protein interaction prediction）</news:title>
   <news:publication_date>2026-07-26T13:10:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716153</loc>
  <lastmod>2026-07-26T13:09:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セットベース適応安全制御の実装と意義（Set-Based Adaptive Safety Control）</news:title>
   <news:publication_date>2026-07-26T13:09:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716151</loc>
  <lastmod>2026-07-26T13:09:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正規化されたフラットミニマの定義（Normalized Flat Minima: Exploring Scale-Invariant Definition of Flat Minima for Neural Networks using PAC-Bayesian Analysis）</news:title>
   <news:publication_date>2026-07-26T13:09:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716149</loc>
  <lastmod>2026-07-26T13:09:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自発的マイクロ表情認識の時空間再帰畳み込みネットワーク（Spatiotemporal Recurrent Convolutional Networks for Recognizing Spontaneous Micro-expressions）</news:title>
   <news:publication_date>2026-07-26T13:09:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716147</loc>
  <lastmod>2026-07-26T13:09:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビデオ広告の効果測定手法（Measuring Effectiveness of Video Advertisements）</news:title>
   <news:publication_date>2026-07-26T13:09:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716145</loc>
  <lastmod>2026-07-26T12:18:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークの内在的スケールは小さい（The Intrinsic Scale Of Networks Is Small）</news:title>
   <news:publication_date>2026-07-26T12:18:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716143</loc>
  <lastmod>2026-07-26T12:18:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意思決定におけるRPS(1)選好のモデル化（Reinforcement-based Probability Shifts in Decision-making）</news:title>
   <news:publication_date>2026-07-26T12:18:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716141</loc>
  <lastmod>2026-07-26T12:17:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Network Lensによるノード分類の新視点（Network Lens: Node Classification in Topologically Heterogeneous Networks）</news:title>
   <news:publication_date>2026-07-26T12:17:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716139</loc>
  <lastmod>2026-07-26T12:16:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な発見的ラジオミクスによる肺がん予測（SISC: End-to-end Interpretable Discovery Radiomics-Driven Lung Cancer Prediction via Stacked Interpretable Sequencing Cells）</news:title>
   <news:publication_date>2026-07-26T12:16:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716137</loc>
  <lastmod>2026-07-26T12:16:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再圧縮画像におけるリサンプリング検出の実務的示唆（Resampling detection of recompressed images via dual-stream convolutional neural network）</news:title>
   <news:publication_date>2026-07-26T12:16:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716135</loc>
  <lastmod>2026-07-26T12:16:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>三重トップクォーク生成から学べること（What can We Learn from Triple Top-Quark Production?）</news:title>
   <news:publication_date>2026-07-26T12:16:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716133</loc>
  <lastmod>2026-07-26T12:15:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己教師あり学習による狭帯域SETIの異常検出（SELF-SUPERVISED ANOMALY DETECTION FOR NARROWBAND SETI）</news:title>
   <news:publication_date>2026-07-26T12:15:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716131</loc>
  <lastmod>2026-07-26T11:24:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンパイラの最適化順序を強化学習で自動化する衝撃（AutoPhase: Compiler Phase-Ordering for HLS with Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-26T11:24:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716129</loc>
  <lastmod>2026-07-26T11:24:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習可能な射影勾配復号法（Deep Learning-Aided Trainable Projected Gradient Decoding for LDPC Codes）</news:title>
   <news:publication_date>2026-07-26T11:24:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716127</loc>
  <lastmod>2026-07-26T11:23:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル・アンサンブルによる一般化ゼロショット学習の革新（Multi-modal Ensemble Classification for Generalized Zero Shot Learning）</news:title>
   <news:publication_date>2026-07-26T11:23:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716125</loc>
  <lastmod>2026-07-26T11:23:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変換を符号化する自己教師なし表現学習（AET vs. AED: Unsupervised Representation Learning by Auto-Encoding Transformations rather than Data）</news:title>
   <news:publication_date>2026-07-26T11:23:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716123</loc>
  <lastmod>2026-07-26T11:23:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多領域画像変換を単一モデルで実現するDual Generator GAN（Dual Generator Generative Adversarial Networks for Multi-Domain Image-to-Image Translation）</news:title>
   <news:publication_date>2026-07-26T11:23:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716121</loc>
  <lastmod>2026-07-26T11:23:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な機械学習の定義と実務的枠組み（Interpretable machine learning: definitions, methods, and applications）</news:title>
   <news:publication_date>2026-07-26T11:23:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716119</loc>
  <lastmod>2026-07-26T11:22:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互情報量に基づく一般化誤差境界の強化（Tightening Mutual Information Based Bounds on Generalization Error）</news:title>
   <news:publication_date>2026-07-26T11:22:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716117</loc>
  <lastmod>2026-07-26T10:31:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の少数ショット学習による合成的指示理解（Human few-shot learning of compositional instructions）</news:title>
   <news:publication_date>2026-07-26T10:31:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716115</loc>
  <lastmod>2026-07-26T10:31:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再生した銀河と非常に古いバルジが示す主系列の湾曲とグリーンヴァレーの起源（Rejuvenated galaxies with very old bulges at the origin of the bending of the main sequence and of the &amp;quot;green valley&amp;quot;）</news:title>
   <news:publication_date>2026-07-26T10:31:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716113</loc>
  <lastmod>2026-07-26T10:30:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模モバイルゲームにおけるマイクロ／マクロ離脱分析（Micro- and Macro-Level Churn Analysis of Large-Scale Mobile Games）</news:title>
   <news:publication_date>2026-07-26T10:30:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716111</loc>
  <lastmod>2026-07-26T10:29:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音楽アーティスト識別の再定義 — 畳み込みリカレントニューラルネットワークによる分類（Music Artist Classification with Convolutional Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-07-26T10:29:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716109</loc>
  <lastmod>2026-07-26T10:29:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己教師あり深層能動型高速MRI（Self-Supervised Deep Active Accelerated MRI）</news:title>
   <news:publication_date>2026-07-26T10:29:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716107</loc>
  <lastmod>2026-07-26T10:29:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインレビューの大規模同時解析：トピック・感情・ユーザ嗜好の統合モデル（Large-Scale Joint Topic, Sentiment &amp;amp; User Preference Analysis for Online Reviews）</news:title>
   <news:publication_date>2026-07-26T10:29:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716105</loc>
  <lastmod>2026-07-26T10:29:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実運用で公平性を測る・改善する方法（Putting Fairness Principles into Practice: Challenges, Metrics, and Improvements）</news:title>
   <news:publication_date>2026-07-26T10:29:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716103</loc>
  <lastmod>2026-07-26T09:37:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>色覚写真からの中心性漿液性網脈絡膜症の検出に関する深層学習の評価（Assessment of central serous chorioretinopathy (CSC) depicted on color fundus photographs using deep Learning）</news:title>
   <news:publication_date>2026-07-26T09:37:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716101</loc>
  <lastmod>2026-07-26T09:37:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CrossNet：非対応画像変換のための潜在クロス整合性（CrossNet: Latent Cross-Consistency for Unpaired Image Translation）</news:title>
   <news:publication_date>2026-07-26T09:37:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716099</loc>
  <lastmod>2026-07-26T09:37:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点単位表現を学ぶPointWise（PointWise: An Unsupervised Point-wise Feature Learning Network）</news:title>
   <news:publication_date>2026-07-26T09:37:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716097</loc>
  <lastmod>2026-07-26T09:35:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EL2Oによる後方分布推定の革新（Posterior inference unchained with EL2O）</news:title>
   <news:publication_date>2026-07-26T09:35:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716095</loc>
  <lastmod>2026-07-26T09:35:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大質量楕円銀河の周囲ガスの詳述（Characterizing circumgalactic gas around massive ellipticals at z ≈0.4 III）</news:title>
   <news:publication_date>2026-07-26T09:35:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716093</loc>
  <lastmod>2026-07-26T09:35:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的数値計算の現代的回顧（A Modern Retrospective on Probabilistic Numerics）</news:title>
   <news:publication_date>2026-07-26T09:35:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716091</loc>
  <lastmod>2026-07-26T09:34:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Z2×Z2オービフォールドの機械学習による分類の試み（Towards machine learning in the classification of Z2 × Z2 orbifold compactifications）</news:title>
   <news:publication_date>2026-07-26T09:34:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716089</loc>
  <lastmod>2026-07-26T08:43:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多ブロック欠損データに対する教師あり学習（Supervised Learning for Multi-Block Incomplete Data）</news:title>
   <news:publication_date>2026-07-26T08:43:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716087</loc>
  <lastmod>2026-07-26T08:34:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CFOF: 次元に強い外れ値スコアの提案（CFOF: A Concentration Free Measure for Anomaly Detection）</news:title>
   <news:publication_date>2026-07-26T08:34:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716085</loc>
  <lastmod>2026-07-26T08:34:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットの構造をベイズで学ぶ（Bayesian Learning of Neural Network Architectures）</news:title>
   <news:publication_date>2026-07-26T08:34:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716083</loc>
  <lastmod>2026-07-26T08:33:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ManiFoolによるマニフォールド探索型データ拡張（Data Augmentation with Manifold Exploring Geometric Transformations for Increased Performance and Robustness）</news:title>
   <news:publication_date>2026-07-26T08:33:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716081</loc>
  <lastmod>2026-07-26T08:33:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>河川氷の深層学習による画素分割（River Ice Segmentation with Deep Learning）</news:title>
   <news:publication_date>2026-07-26T08:33:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716079</loc>
  <lastmod>2026-07-26T08:33:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイク遅延可塑性(STDP)で学ぶ視覚特徴学習の現状（Unsupervised Visual Feature Learning with Spike-timing-dependent Plasticity: How Far are we from Traditional Feature Learning Approaches?）</news:title>
   <news:publication_date>2026-07-26T08:33:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716077</loc>
  <lastmod>2026-07-26T08:32:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小電極での発作検出を目指すCNNモデルの提案（SEIZURE DETECTION USING LEAST EEG CHANNELS BY DEEP CONVOLUTIONAL NEURAL NETWORK）</news:title>
   <news:publication_date>2026-07-26T08:32:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716075</loc>
  <lastmod>2026-07-26T07:41:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈依存記号をCTCで使うための工夫（Towards using context-dependent symbols in CTC without state-tying decision trees）</news:title>
   <news:publication_date>2026-07-26T07:41:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716073</loc>
  <lastmod>2026-07-26T07:41:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データサイエンティストのための倫理指針へのアプローチ (Approaching Ethical Guidelines for Data Scientists)</news:title>
   <news:publication_date>2026-07-26T07:41:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716071</loc>
  <lastmod>2026-07-26T07:41:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メールの「後回し（Deferral）」を読み解く――受信箱を賢く支援するための行動分析と予測（Characterizing and Predicting Email Deferral Behavior）</news:title>
   <news:publication_date>2026-07-26T07:41:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716069</loc>
  <lastmod>2026-07-26T07:40:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付きディープラーニングを用いた新しいトポロジ最適化手法（A Novel Topology Optimization Approach using Conditional Deep Learning）</news:title>
   <news:publication_date>2026-07-26T07:40:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716067</loc>
  <lastmod>2026-07-26T07:40:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M15球状星団における深部観測と示唆（Deep observations of the globular cluster M15 with the MAGIC telescopes）</news:title>
   <news:publication_date>2026-07-26T07:40:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716065</loc>
  <lastmod>2026-07-26T07:40:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低帯域ネットワーク向けのグローバルトップkスパース化を用いた分散同期SGDアルゴリズム（A Distributed Synchronous SGD Algorithm with Global Top-k Sparsiﬁcation for Low Bandwidth Networks）</news:title>
   <news:publication_date>2026-07-26T07:40:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716063</loc>
  <lastmod>2026-07-26T07:40:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己修正型ディープラーニングによる集中治療領域の急性事象予測（A Self-Correcting Deep Learning Approach to Predict Acute Conditions in Critical Care）</news:title>
   <news:publication_date>2026-07-26T07:40:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716061</loc>
  <lastmod>2026-07-26T06:49:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深宇宙で粒子を精密に測る計器の設計思想（Penetrating particle ANalyzer (PAN)）</news:title>
   <news:publication_date>2026-07-26T06:49:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716059</loc>
  <lastmod>2026-07-26T06:48:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復型深層学習を用いたヒューマン・イン・ザ・ループ型の非バイアス立体計測（Iterative Deep Learning Based Unbiased Stereology With Human-in-the-Loop）</news:title>
   <news:publication_date>2026-07-26T06:48:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716057</loc>
  <lastmod>2026-07-26T06:48:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二値ペアワイズ・マルコフネットワークの高次元構造学習比較（High-dimensional structure learning of binary pairwise Markov networks: A comparative numerical study）</news:title>
   <news:publication_date>2026-07-26T06:48:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716055</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-26T06:48:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716053</loc>
  <lastmod>2026-07-26T06:47:48Z</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/716051</loc>
  <lastmod>2026-07-26T06:47:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716049</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>低リソース感情音声合成のための転移学習の探究（Exploring Transfer Learning for Low Resource Emotional TTS）</news:title>
   <news:publication_date>2026-07-26T06:47:15Z</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>
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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>
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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>
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   </news:publication>
   <news:title>地区熱供給における熱負荷パターンの発見（A data-driven approach for discovering heat load patterns in district heating）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716041</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>ラベル誤りに強くなるための「意見不一致」の効用（How does Disagreement Help Generalization against Label Corruption?）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716039</loc>
  <lastmod>2026-07-26T05:54:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Tango: 軽量で移植性の高いDNNベンチマークスイート（Tango: A Deep Neural Network Benchmark Suite for Various Accelerators）</news:title>
   <news:publication_date>2026-07-26T05:54:28Z</news:publication_date>
   <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>幾何光学で読み解く制約下ブラウニアン運動の短篇三題（Geometrical optics of constrained Brownian motion: three short stories）</news:title>
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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>重力場モデリングのための最良基底学習への第一歩（A first approach to learning a best basis for gravity field modelling）</news:title>
   <news:publication_date>2026-07-26T05:53:46Z</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>Deep Logic Modelsによる学習と推論の統合（Integrating Learning and Reasoning with Deep Logic Models）</news:title>
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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>マルチバンド加重lpノルム最小化による画像ノイズ除去（Multi-band Weighted lp Norm Minimization for Image Denoising）</news:title>
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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>
   <news:title>高齢期の社会参加を促す技術（Technologies for Promoting Social Participation in Later Life）</news:title>
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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>
   <news:title>材料科学におけるシンボリック回帰（Symbolic regression in materials science）</news:title>
   <news:publication_date>2026-07-26T05:01:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716025</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>惑星状星雲PHR 1315-6555の中心星と母天団AL 1の再評価（The Central Star of Planetary Nebula PHR 1315-6555 and its host Galactic Open Cluster AL 1）</news:title>
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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>学習データ削減による深層学習テストの高速化（Towards Testing of Deep Learning Systems with Training Set Reduction）</news:title>
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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>
  </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>ベイズ更新によるプロジェクト固有資産の取得と意思決定（Acquisition of Project-Specific Assets with Bayesian Updating）</news:title>
   <news:publication_date>2026-07-26T04:08:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716017</loc>
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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>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716015</loc>
  <lastmod>2026-07-26T04:08:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子モデルから学習した短距離秩序構造モチーフ（Short-Range Order Structure Motifs Learned from an Atomistic Model of a Zr50Cu45Al5 Metallic Glass）</news:title>
   <news:publication_date>2026-07-26T04:08:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716013</loc>
  <lastmod>2026-07-26T04:06:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カップル心理療法における音声感情認識の実証（Machine learning for the recognition of emotion in the speech of couples in psychotherapy using the Stanford Suppes Brain Lab Psychotherapy Dataset）</news:title>
   <news:publication_date>2026-07-26T04:06:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716011</loc>
  <lastmod>2026-07-26T04:06:09Z</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>2026-07-26T04:06:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/716009</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>ワイヤレスチャネルの“もごもご”予測（Predicting the Mumble of Wireless Channel with Sequence-to-Sequence Models）</news:title>
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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>
  </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>属性付きネットワーク埋め込みの新展開（Attributed Network Embedding via Subspace Discovery）</news:title>
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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>
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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>
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   </news:publication>
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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>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715997</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>ラベルの少ない環境で評価コストを抑える勾配正則化予算付きブースティング（Gradient Regularized Budgeted Boosting）</news:title>
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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>Residual-CNDSによる大規模シーン分類の安定化（Residual-CNDS for Grand Challenge Scene Dataset）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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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:title>Gradient Boosted Feature Selection（Gradient Boosted Feature Selection）</news:title>
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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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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
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 </url>
 <url>
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  <news:news>
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    <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:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neumannネットワークによる線形逆問題の解法（Neumann Networks for Linear Inverse Problems in Imaging）</news:title>
   <news:publication_date>2026-07-26T02:18:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715981</loc>
  <lastmod>2026-07-26T02:17:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックボックス関数インターフェースの学習（NEURAL NETWORK GRADIENT-BASED LEARNING OF BLACK-BOX FUNCTION INTERFACES）</news:title>
   <news:publication_date>2026-07-26T02:17:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715979</loc>
  <lastmod>2026-07-26T02:17:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散マイクロサービスの自己適応に向けた深層リカレントQネットワーク（A Deep Recurrent Q Network towards Self-adapting Distributed Microservices architecture）</news:title>
   <news:publication_date>2026-07-26T02:17:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715977</loc>
  <lastmod>2026-07-26T01:26:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細密スケッチのためのRNNベース生成モデル（RNN-based Generative Model for Fine-Grained Sketching）</news:title>
   <news:publication_date>2026-07-26T01:26:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715975</loc>
  <lastmod>2026-07-26T01:25:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハービッグAe/Be星における磁気圏降着の検証（Examining magnetospheric accretion in Herbig Ae/Be stars through near-infrared spectroscopic signatures）</news:title>
   <news:publication_date>2026-07-26T01:25:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715973</loc>
  <lastmod>2026-07-26T01:25:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウイルス殻形成のフィットネス地形を機械学習で解析する（Machine-learning a virus assembly fitness landscape）</news:title>
   <news:publication_date>2026-07-26T01:25:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715971</loc>
  <lastmod>2026-07-26T01:24:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的テクスチャのための完全ベイズ無限生成モデル（A Fully Bayesian Infinite Generative Model for Dynamic Texture Segmentation）</news:title>
   <news:publication_date>2026-07-26T01:24:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715969</loc>
  <lastmod>2026-07-26T01:23:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一クラス学習で指紋偽造検出を一般化する（Generalizing Fingerprint Spoof Detector: Learning a One-Class Classifier）</news:title>
   <news:publication_date>2026-07-26T01:23:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715967</loc>
  <lastmod>2026-07-26T01:23:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師あり回帰におけるクラスタアンサンブルと低ランク共同行列分解による不確実性下での予測改善（Semi-Supervised Regression using Cluster Ensemble and Low-Rank Co-Association Matrix Decomposition under Uncertainties）</news:title>
   <news:publication_date>2026-07-26T01:23:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715965</loc>
  <lastmod>2026-07-26T01:22:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラグランジュ軌跡シミュレーションのための生成対向ネットワークモデルの導入（Introducing a Generative Adversarial Network Model for Lagrangian Trajectory Simulation）</news:title>
   <news:publication_date>2026-07-26T01:22:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715963</loc>
  <lastmod>2026-07-26T00:31:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転向けリアルタイム物体検出とセマンティックセグメンテーションの統合ネットワーク（Real-time Joint Object Detection and Semantic Segmentation Network for Automated Driving）</news:title>
   <news:publication_date>2026-07-26T00:31:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715961</loc>
  <lastmod>2026-07-26T00:31:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化されたフォトリアリスティックなスタイル転送（Automated Deep Photo Style Transfer）</news:title>
   <news:publication_date>2026-07-26T00:31:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715959</loc>
  <lastmod>2026-07-26T00:30:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全ての悪い局所最適を消す手法の要点（Eliminating All Bad Local Minima from Loss Landscapes Without Even Adding an Extra Unit）</news:title>
   <news:publication_date>2026-07-26T00:30:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715957</loc>
  <lastmod>2026-07-26T00:29:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数データビューのクラスタリングは独立か？（Are Clusterings of Multiple Data Views Independent?）</news:title>
   <news:publication_date>2026-07-26T00:29:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715955</loc>
  <lastmod>2026-07-26T00:29:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列3D医療画像のためのクロスモーダルニューラルネットワーク（CHRONOMID: cross-modal neural networks for 3-d temporal medical imaging data）</news:title>
   <news:publication_date>2026-07-26T00:29:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715953</loc>
  <lastmod>2026-07-26T00:29:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペルシア語における発話行為分類と誤情報検出への応用（A Speech Act Classifier for Persian Texts and its Application in Identifying Rumors）</news:title>
   <news:publication_date>2026-07-26T00:29:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715951</loc>
  <lastmod>2026-07-26T00:28:55Z</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再結合（Recombination of Artificial Neural Networks）</news:title>
   <news:publication_date>2026-07-26T00:28:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715949</loc>
  <lastmod>2026-07-25T23:37:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応型誘導と強化学習によるメタ学習（ADAPTIVE GUIDANCE WITH REINFORCEMENT META-LEARNING）</news:title>
   <news:publication_date>2026-07-25T23:37:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715947</loc>
  <lastmod>2026-07-25T23:37:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人種別に最適化する大腸がん生存予測モデル（Personalized Colorectal Cancer Survivability Prediction with Machine Learning Methods）</news:title>
   <news:publication_date>2026-07-25T23:37:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715945</loc>
  <lastmod>2026-07-25T23:37:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元軌跡の長期正確予測の学習（Learning Accurate Extended-Horizon Predictions of High Dimensional Trajectories）</news:title>
   <news:publication_date>2026-07-25T23:37:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715943</loc>
  <lastmod>2026-07-25T23:36:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高容量画像ステガノグラフィを実現するSteganoGAN（SteganoGAN: High Capacity Image Steganography with GANs）</news:title>
   <news:publication_date>2026-07-25T23:36:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715941</loc>
  <lastmod>2026-07-25T23:36:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッド推薦システムの体系的文献レビュー (Hybrid Recommender Systems: A Systematic Literature Review)</news:title>
   <news:publication_date>2026-07-25T23:36:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715939</loc>
  <lastmod>2026-07-25T23:35:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地層ファシーズ分類のための機械学習ベンチマーク（A Machine Learning Benchmark for Facies Classification）</news:title>
   <news:publication_date>2026-07-25T23:35:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715937</loc>
  <lastmod>2026-07-25T23:35:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共有メモリで学ぶ協調行動 ― 小規模マルチエージェント強化学習における記憶駆動型通信（IMPROVING COORDINATION IN SMALL-SCALE MULTI-AGENT DEEP REINFORCEMENT LEARNING THROUGH MEMORY-DRIVEN COMMUNICATION）</news:title>
   <news:publication_date>2026-07-25T23:35:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715935</loc>
  <lastmod>2026-07-25T22:44:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HorizonNetによる室内レイアウト推定（HorizonNet: Learning Room Layout with 1D Representation and Pano Stretch）</news:title>
   <news:publication_date>2026-07-25T22:44:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715933</loc>
  <lastmod>2026-07-25T22:34:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチプレイヤーバンディットによる最適割当と異種報酬（Multi-player Bandits for Optimal Assignment with Heterogeneous Rewards）</news:title>
   <news:publication_date>2026-07-25T22:34:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715931</loc>
  <lastmod>2026-07-25T22:33:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RRAMに基づくニューロモルフィックアルゴリズム（RRAM based neuromorphic algorithms）</news:title>
   <news:publication_date>2026-07-25T22:33:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715929</loc>
  <lastmod>2026-07-25T22:33:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顎嚢胞病変における深層学習による角化嚢胞（odontogenic keratocyst）同定の実用性（Deep-learning-based identification of odontogenic keratocysts in hematoxylin- and eosin-stained jaw cyst specimens）</news:title>
   <news:publication_date>2026-07-25T22:33:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715927</loc>
  <lastmod>2026-07-25T22:33:14Z</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説明性を高める設計制約（Enhancing Explainability of Neural Networks through Architecture Constraints）</news:title>
   <news:publication_date>2026-07-25T22:33:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715925</loc>
  <lastmod>2026-07-25T22:33:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大量の放送ビデオデータの要約と可視化（Summarization and Visualization of Large Volumes of Broadcast Video Data）</news:title>
   <news:publication_date>2026-07-25T22:33:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715923</loc>
  <lastmod>2026-07-25T22:32:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続音声に埋もれたキーワードを少量データで見つける（Prototypical Metric Transfer Learning for Continuous Speech Keyword Spotting with Limited Training Data）</news:title>
   <news:publication_date>2026-07-25T22:32:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715921</loc>
  <lastmod>2026-07-25T21:41:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ALiPy: Active Learning in Python（ALiPy: Active Learning in Python）</news:title>
   <news:publication_date>2026-07-25T21:41:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715919</loc>
  <lastmod>2026-07-25T21:31:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現学習を用いた拡散到達確率の予測（Predicting Diffusion Reach Probabilities via Representation Learning on Social Networks）</news:title>
   <news:publication_date>2026-07-25T21:31:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715917</loc>
  <lastmod>2026-07-25T21:31:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統計物理から読み解く「臨界温度」を深層学習が刻む仕組み（Logical Reasoning for Revealing the Critical Temperature through Deep Learning of Configuration Ensemble of Statistical Systems）</news:title>
   <news:publication_date>2026-07-25T21:31:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715915</loc>
  <lastmod>2026-07-25T21:31:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ECGに対する敵対的攻撃の実践的検証（ECGadv: Generating Adversarial Electrocardiogram to Misguide Arrhythmia Classification System）</news:title>
   <news:publication_date>2026-07-25T21:31:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715913</loc>
  <lastmod>2026-07-25T21:30:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群衆シーンにおける物体検出のための対（ペア）関係学習（Learning Pairwise Relationship for Multi-object Detection in Crowded Scenes）</news:title>
   <news:publication_date>2026-07-25T21:30:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715911</loc>
  <lastmod>2026-07-25T21:30:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己教師付き学習による3D人体姿勢推定の実用化突破（3D Human Pose Machines with Self-supervised Learning）</news:title>
   <news:publication_date>2026-07-25T21:30:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715909</loc>
  <lastmod>2026-07-25T21:30:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学生の感情ラベリングにおける社会文化差の重要性（The Importance of Socio-Cultural Differences for Annotating and Detecting the Affective States of Students）</news:title>
   <news:publication_date>2026-07-25T21:30:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715907</loc>
  <lastmod>2026-07-25T20:39:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分的な解釈から学ぶ地震イメージ分類（Automatic classification of geologic units in seismic images using partially interpreted examples）</news:title>
   <news:publication_date>2026-07-25T20:39:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715905</loc>
  <lastmod>2026-07-25T20:39:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタリングとFP-Growthを用いたデング熱高発生学習（Learning of High Dengue Incidence with Clustering and FP-Growth Algorithm using WHO Historical Data）</news:title>
   <news:publication_date>2026-07-25T20:39:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715903</loc>
  <lastmod>2026-07-25T20:38:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメトリック曲線・曲面のデータ駆動再構成（DeepSpline: Data-Driven Reconstruction of Parametric Curves and Surfaces）</news:title>
   <news:publication_date>2026-07-25T20:38:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715901</loc>
  <lastmod>2026-07-25T20:37:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化Radon変換を用いた線形・非線形多様体上の非パラメトリック密度推定（On non-parametric density estimation on linear and non-linear manifolds using generalized Radon transforms）</news:title>
   <news:publication_date>2026-07-25T20:37:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715899</loc>
  <lastmod>2026-07-25T20:37:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Numpyアプリケーションの自動高速化（Automatic acceleration of Numpy applications on GPUs and multicore CPUs）</news:title>
   <news:publication_date>2026-07-25T20:37:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715897</loc>
  <lastmod>2026-07-25T20:37:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予算最適化型クラウド作業者割当（BUOCA: Budget-Optimized Crowd Worker Allocation）</news:title>
   <news:publication_date>2026-07-25T20:37:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715895</loc>
  <lastmod>2026-07-25T20:37:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力優先度付けによるニューラルネットワーク検査の効率化（Input Prioritization for Testing Neural Networks）</news:title>
   <news:publication_date>2026-07-25T20:37:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715893</loc>
  <lastmod>2026-07-25T19:45:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープなほど良い：人物属性認識の分析（The Deeper, the Better: Analysis of Person Attributes Recognition）</news:title>
   <news:publication_date>2026-07-25T19:45:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715891</loc>
  <lastmod>2026-07-25T19:45:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層モデルベース強化学習によるクアドロータの低レベル制御 (Low Level Control of a Quadrotor with Deep Model-Based Reinforcement Learning)</news:title>
   <news:publication_date>2026-07-25T19:45:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715889</loc>
  <lastmod>2026-07-25T19:45:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EQUATE：自然言語推論における定量的推論評価フレームワーク（EQUATE: A Benchmark Evaluation Framework for Quantitative Reasoning in Natural Language Inference）</news:title>
   <news:publication_date>2026-07-25T19:45:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715887</loc>
  <lastmod>2026-07-25T19:44:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所的固有次元に適応する非パラメトリック推論（Non-Parametric Inference Adaptive to Intrinsic Dimension）</news:title>
   <news:publication_date>2026-07-25T19:44:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715885</loc>
  <lastmod>2026-07-25T19:44:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河バルジの化石遺物 HP 1 の深い観測（A Deep View of a Fossil Relic in the Galactic Bulge: The Globular Cluster HP 1）</news:title>
   <news:publication_date>2026-07-25T19:44:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715883</loc>
  <lastmod>2026-07-25T19:43:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データセットプルーニングが機械学習に与える影響（Impact of Data Pruning on Machine Learning Algorithm Performance）</news:title>
   <news:publication_date>2026-07-25T19:43:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715881</loc>
  <lastmod>2026-07-25T19:43:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光学フローを用いた意味的セグメンテーションの強化（Optical Flow augmented Semantic Segmentation networks for Automated Driving）</news:title>
   <news:publication_date>2026-07-25T19:43:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715879</loc>
  <lastmod>2026-07-25T18:52:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低消費電力ニューロモルフィックハードウェアによる信号処理応用（Low-Power Neuromorphic Hardware for Signal Processing Applications）</news:title>
   <news:publication_date>2026-07-25T18:52:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715877</loc>
  <lastmod>2026-07-25T18:51:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習の大規模比較を自動化する仕組み（Machine Learning Automation Toolbox (MLaut))</news:title>
   <news:publication_date>2026-07-25T18:51:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715875</loc>
  <lastmod>2026-07-25T18:42:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒストパソロジ画像における多層バッチ正規化による浸潤性乳管癌（Invasive Ductal Carcinoma）セル識別（MULTI-LEVEL BATCH NORMALIZATION IN DEEP NETWORKS FOR INVASIVE DUCTAL CARCINOMA CELL DISCRIMINATION IN HISTOPATHOLOGY IMAGES）</news:title>
   <news:publication_date>2026-07-25T18:42:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715873</loc>
  <lastmod>2026-07-25T18:41:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転向け深層スパイキングニューラルネットワークの意義（Exploring Deep Spiking Neural Networks for Automated Driving Applications）</news:title>
   <news:publication_date>2026-07-25T18:41:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715871</loc>
  <lastmod>2026-07-25T18:40:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>模倣学習の大域的収束性とLQRにおける示唆（On the Global Convergence of Imitation Learning: A Case for Linear Quadratic Regulator）</news:title>
   <news:publication_date>2026-07-25T18:40:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715869</loc>
  <lastmod>2026-07-25T18:40:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模商品埋め込みを用いた協調フィルタリング（Large-scale Collaborative Filtering with Product Embeddings）</news:title>
   <news:publication_date>2026-07-25T18:40:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715867</loc>
  <lastmod>2026-07-25T18:39:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>麻とポリプロピレン複合材の機械特性をANNで推定する研究（Determining the Mechanical Properties of a New Composite Material using Artificial Neural Networks）</news:title>
   <news:publication_date>2026-07-25T18:39:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715865</loc>
  <lastmod>2026-07-25T17:48:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>星間探査機がもたらす天文学・宇宙物理学への利益 (Interstellar Probes: The Benefits to Astronomy and Astrophysics)</news:title>
   <news:publication_date>2026-07-25T17:48:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715863</loc>
  <lastmod>2026-07-25T17:48:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Variation Network：入力の高次属性を制御する生成モデル（Variation Network: Learning High-level Attributes for Controlled Input Manipulation）</news:title>
   <news:publication_date>2026-07-25T17:48:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715861</loc>
  <lastmod>2026-07-25T17:48:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による推定確率密度関数モデル（Deep learning for presumed probability density function models）</news:title>
   <news:publication_date>2026-07-25T17:48:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715859</loc>
  <lastmod>2026-07-25T17:47:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セルラー大規模MIMOにおける可変ユーザ活動下の電力制御（Power Control in Cellular Massive MIMO with Varying User Activity: A Deep Learning Solution）</news:title>
   <news:publication_date>2026-07-25T17:47:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715857</loc>
  <lastmod>2026-07-25T17:47:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高忠実度な画像間翻訳の分離と非協調的再結合（Image Disentanglement and Uncooperative Re-Entanglement for High-Fidelity Image-to-Image Translation）</news:title>
   <news:publication_date>2026-07-25T17:47:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715855</loc>
  <lastmod>2026-07-25T17:46:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期化時の過剰パラメータ化がもたらす利点（THE BENEFITS OF OVER-PARAMETERIZATION AT INITIALIZATION IN DEEP RELU NETWORKS）</news:title>
   <news:publication_date>2026-07-25T17:46:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715853</loc>
  <lastmod>2026-07-25T17:46:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相関する情報源からのサイド情報を用いた普遍圧縮（Universal Compression with Side Information from a Correlated Source）</news:title>
   <news:publication_date>2026-07-25T17:46:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715851</loc>
  <lastmod>2026-07-25T16:55:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SPFlow：Sum-Product Networksを手軽に扱うための拡張可能なライブラリ（SPFlow: AN EASY AND EXTENSIBLE LIBRARY FOR DEEP PROBABILISTIC LEARNING USING SUM-PRODUCT NETWORKS）</news:title>
   <news:publication_date>2026-07-25T16:55:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715849</loc>
  <lastmod>2026-07-25T16:55:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習のマルウェアバイナリに対する脆弱性の解明（Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries）</news:title>
   <news:publication_date>2026-07-25T16:55:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715847</loc>
  <lastmod>2026-07-25T16:55:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実運用に迫る背景差分の実態と課題（Background Subtraction in Real Applications: Challenges, Current Models and Future Directions）</news:title>
   <news:publication_date>2026-07-25T16:55:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715845</loc>
  <lastmod>2026-07-25T16:54:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DIVE：脳病変の時空間進行モデル（DIVE: A spatiotemporal progression model of brain pathology in neurodegenerative disorders）</news:title>
   <news:publication_date>2026-07-25T16:54:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715843</loc>
  <lastmod>2026-07-25T16:53:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Biomedical Image Reconstruction: From the Foundations to Deep Neural Networks（Biomedical Image Reconstruction: From the Foundations to Deep Neural Networks）</news:title>
   <news:publication_date>2026-07-25T16:53:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715841</loc>
  <lastmod>2026-07-25T16:53:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非把持操作のための操作状態と行動の学習（Learning Manipulation States and Actions for Efficient Non-prehensile Rearrangement Planning）</news:title>
   <news:publication_date>2026-07-25T16:53:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715839</loc>
  <lastmod>2026-07-25T16:53:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルを持たない計画の探究（An Investigation of Model-free Planning）</news:title>
   <news:publication_date>2026-07-25T16:53:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715837</loc>
  <lastmod>2026-07-25T16:02:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>堅牢なパッチ照合のための特徴融合とコンパクト二値記述子（Feature Fusion for Robust Patch Matching With Compact Binary Descriptors）</news:title>
   <news:publication_date>2026-07-25T16:02:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715835</loc>
  <lastmod>2026-07-25T16:02:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化比較試験における予後指標に基づく教師あり変数選択（Supervised variable selection in randomized controlled trials prior to exploration of treatment effect heterogeneity）</news:title>
   <news:publication_date>2026-07-25T16:02:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715833</loc>
  <lastmod>2026-07-25T16:01:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>類似商品画像検索のための深層学習手法（Retrieving Similar E-Commerce Images Using Deep Learning）</news:title>
   <news:publication_date>2026-07-25T16:01:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715831</loc>
  <lastmod>2026-07-25T16:00:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FishNet: 画像・領域・画素レベル予測に応用可能なバックボーン（FishNet: A Versatile Backbone for Image, Region, and Pixel Level Prediction）</news:title>
   <news:publication_date>2026-07-25T16:00:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715829</loc>
  <lastmod>2026-07-25T16:00:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中国宇宙ステーション光学サーベイの有効銀河数解析（The analysis of effective galaxies number count for Chinese Space Station Optical Survey (CSS-OS) by image simulation）</news:title>
   <news:publication_date>2026-07-25T16:00:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715827</loc>
  <lastmod>2026-07-25T15:59:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>疾患知識の転移――神経変性疾患間の知見共有（Disease Knowledge Transfer across Neurodegenerative Diseases）</news:title>
   <news:publication_date>2026-07-25T15:59:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715825</loc>
  <lastmod>2026-07-25T15:59:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報探索対話におけるユーザ意図予測（User Intent Prediction in Information-seeking Conversations）</news:title>
   <news:publication_date>2026-07-25T15:59:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715823</loc>
  <lastmod>2026-07-25T15:07:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Hawking放射を模す単純模型（A simple model for Hawking radiation）</news:title>
   <news:publication_date>2026-07-25T15:07:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715821</loc>
  <lastmod>2026-07-25T15:07:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>応答面のランク付けを深層学習で解く（Deep Learning for Ranking Response Surfaces with Applications to Optimal Stopping Problems）</news:title>
   <news:publication_date>2026-07-25T15:07:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715819</loc>
  <lastmod>2026-07-25T15:07:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LGANによるCT画像の肺領域分割（LGAN: Lung Segmentation in CT Scans）</news:title>
   <news:publication_date>2026-07-25T15:07:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715817</loc>
  <lastmod>2026-07-25T15:07:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深度カメラ画像からの手領域分割と指先追跡（Hand Segmentation and Fingertip Tracking from Depth Camera Images Using Deep Convolutional Neural Network and Multi-task SegNet）</news:title>
   <news:publication_date>2026-07-25T15:07:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715815</loc>
  <lastmod>2026-07-25T15:06:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ルービックキューブの色認識をロバストにする（COLOR RECOGNITION FOR RUBIK’S CUBE ROBOT）</news:title>
   <news:publication_date>2026-07-25T15:06:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715813</loc>
  <lastmod>2026-07-25T15:06:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイムな地震信号と雑音の識別を機械学習で高精度に行う方法（Reliable Real-time Seismic Signal/Noise Discrimination with Machine Learning）</news:title>
   <news:publication_date>2026-07-25T15:06:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715811</loc>
  <lastmod>2026-07-25T15:05:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムネットワークにおける重要ノード選択の効率的サンプリング（Efficient Sampling for Selecting Important Nodes in Random Network）</news:title>
   <news:publication_date>2026-07-25T15:05:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715809</loc>
  <lastmod>2026-07-25T14:14:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストーリー終局生成の強化型ポインタジェネレータ（From Plots to Endings: A Reinforced Pointer Generator for Story Ending Generation）</news:title>
   <news:publication_date>2026-07-25T14:14:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715807</loc>
  <lastmod>2026-07-25T14:14:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>投影データから学ぶ画像再構成：スパースビューCTの全自動再構成ネット（Learning image from projection: a full-automatic reconstruction (FAR) net for sparse-views computed tomography）</news:title>
   <news:publication_date>2026-07-25T14:14:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715805</loc>
  <lastmod>2026-07-25T14:13:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>日常機器で可能になる音響センシングの全体像（Ubiquitous Acoustic Sensing on Commodity IoT Devices: A Survey）</news:title>
   <news:publication_date>2026-07-25T14:13:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715803</loc>
  <lastmod>2026-07-25T14:12:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無向グラフィカルモデルを近似事後分布として用いる試み（Undirected Graphical Models as Approximate Posteriors）</news:title>
   <news:publication_date>2026-07-25T14:12:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715801</loc>
  <lastmod>2026-07-25T14:12:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MIMO通信におけるDNNベースのkステップ予測を用いた決定指向チャネル推定（Decision Directed Channel Estimation Based on Deep Neural Network k-step Predictor for MIMO Communications in 5G）</news:title>
   <news:publication_date>2026-07-25T14:12:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715799</loc>
  <lastmod>2026-07-25T14:12:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>現代ニューラルネットワークのチューリング完全性（ON THE TURING COMPLETENESS OF MODERN NEURAL NETWORK ARCHITECTURES）</news:title>
   <news:publication_date>2026-07-25T14:12:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715797</loc>
  <lastmod>2026-07-25T14:11:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ特徴の学習と抽出に関するレビュー（REVIEW ON LEARNING AND EXTRACTING GRAPH FEATURES FOR LINK PREDICTION）</news:title>
   <news:publication_date>2026-07-25T14:11:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715795</loc>
  <lastmod>2026-07-25T13:20:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>病変を中心に超解像を作る――医用単一画像SISRに対する病変焦点型マルチスケールGANの提案（HOW CAN WE MAKE GAN PERFORM BETTER IN SINGLE MEDICAL IMAGE SUPER-RESOLUTION? A LESION FOCUSED MULTI-SCALE APPROACH）</news:title>
   <news:publication_date>2026-07-25T13:20:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715793</loc>
  <lastmod>2026-07-25T13:20:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Posterior Collapseを防ぐδ-VAEの実践的解説（PREVENTING POSTERIOR COLLAPSE WITH δ-VAES）</news:title>
   <news:publication_date>2026-07-25T13:20:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715791</loc>
  <lastmod>2026-07-25T13:20:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈認識型機械学習（Context Aware Machine Learning）</news:title>
   <news:publication_date>2026-07-25T13:20:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715789</loc>
  <lastmod>2026-07-25T13:19:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による異常検知の概観（DEEP LEARNING FOR ANOMALY DETECTION: A SURVEY）</news:title>
   <news:publication_date>2026-07-25T13:19:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715787</loc>
  <lastmod>2026-07-25T13:18:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手作り特徴量と深層学習によるスケーラブルな動画QoEモデリング（Handcrafted vs Deep Learning Classification for Scalable Video QoE Modeling）</news:title>
   <news:publication_date>2026-07-25T13:18:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715785</loc>
  <lastmod>2026-07-25T13:18:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>1ビット測定からの平均推定（Mean Estimation from One-Bit Measurements）</news:title>
   <news:publication_date>2026-07-25T13:18:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715783</loc>
  <lastmod>2026-07-25T13:18:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オフライン手書き署名認証における敵対的事例の特徴付けと評価（Characterizing and evaluating adversarial examples for Offline Handwritten Signature Verification）</news:title>
   <news:publication_date>2026-07-25T13:18:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715781</loc>
  <lastmod>2026-07-25T12:27:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>干ばつ予測における混合モデルとニューラルネットワークの実務的適用（A mixed model approach to drought prediction using artificial neural networks）</news:title>
   <news:publication_date>2026-07-25T12:27:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715779</loc>
  <lastmod>2026-07-25T12:26:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>状態マスキング下のMIMOブロードキャスト通信（Broadcasting Information subject to State Masking over a MIMO State Dependent Gaussian Channel）</news:title>
   <news:publication_date>2026-07-25T12:26:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715777</loc>
  <lastmod>2026-07-25T12:26:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>擬似健常画像合成における病変の因子分解の重要性（Adversarial Pseudo Healthy Synthesis Needs Pathology Factorization）</news:title>
   <news:publication_date>2026-07-25T12:26:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715775</loc>
  <lastmod>2026-07-25T12:26:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーパラメータ不明下で後悔しないベイズ最適化（No-Regret Bayesian Optimization with Unknown Hyperparameters）</news:title>
   <news:publication_date>2026-07-25T12:26:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715773</loc>
  <lastmod>2026-07-25T12:25:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RetinaMaskによる単発検出器の精度向上（RetinaMask: Learning to predict masks improves state-of-the-art single-shot detection for free）</news:title>
   <news:publication_date>2026-07-25T12:25:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715771</loc>
  <lastmod>2026-07-25T12:25:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈情報分離による教師なし移動物体検出（Unsupervised Moving Object Detection via Contextual Information Separation）</news:title>
   <news:publication_date>2026-07-25T12:25:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-07-25T12:25:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>開発者識別エラーを能動学習で解消する手法の提案（ALFAA: Active Learning Fingerprint Based Anti-Aliasing for Correcting Developer Identity Errors in Version Control Data）</news:title>
   <news:publication_date>2026-07-25T12:25:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715767</loc>
  <lastmod>2026-07-25T11:34:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所トポロジカル不変量の機械学習による測定（Machine learning assisted measurement of local topological invariants）</news:title>
   <news:publication_date>2026-07-25T11:34:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715765</loc>
  <lastmod>2026-07-25T11:33:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率分布上の加速フロー（Accelerated Flow for Probability Distributions）</news:title>
   <news:publication_date>2026-07-25T11:33:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715763</loc>
  <lastmod>2026-07-25T11:33:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Type Ibn超新星は必ずしも大質量星に由来しないかもしれない（Type Ibn Supernovae May not all Come from Massive Stars）</news:title>
   <news:publication_date>2026-07-25T11:33:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715761</loc>
  <lastmod>2026-07-25T11:33:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>代理モデル支援信頼性設計最適化の総説と新しい一般的枠組み (Surrogate-assisted reliability-based design optimization: a survey and a new general framework)</news:title>
   <news:publication_date>2026-07-25T11:33:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715759</loc>
  <lastmod>2026-07-25T11:32:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>洪水後の通行可能道路の自動検出（Automatic detection of passable roads after floods in remote sensed and social media data）</news:title>
   <news:publication_date>2026-07-25T11:32:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715757</loc>
  <lastmod>2026-07-25T11:32:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>普遍的な密度行列汎関数の構築（A Universal Density Matrix Functional from Molecular Orbital-Based Machine Learning: Transferability across Organic Molecules）</news:title>
   <news:publication_date>2026-07-25T11:32:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715755</loc>
  <lastmod>2026-07-25T11:32:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多波長・高分解能ハイパースペクトル画像融合の新展開（Multispectral and Hyperspectral Image Fusion by MS/HS Fusion Net）</news:title>
   <news:publication_date>2026-07-25T11:32:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715753</loc>
  <lastmod>2026-07-25T10:41:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スムージングスプライン半準パラメトリック密度モデル（Smoothing Spline Semiparametric Density Models）</news:title>
   <news:publication_date>2026-07-25T10:41:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715751</loc>
  <lastmod>2026-07-25T10:40:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部屋分類器のためのデータ増強に関するGAN活用法（DATA AUGMENTATION OF ROOM CLASSIFIERS USING GENERATIVE ADVERSARIAL NETWORKS）</news:title>
   <news:publication_date>2026-07-25T10:40:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715749</loc>
  <lastmod>2026-07-25T10:40:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分裂顆粒の木構造と深部の下向流の関係（Link between trees of fragmenting granules and deep downflows in MHD simulation）</news:title>
   <news:publication_date>2026-07-25T10:40:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715747</loc>
  <lastmod>2026-07-25T10:39:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランク半正定値計画を古典的に亜線形時間で解く手法（Quantum-inspired sublinear algorithm for solving low-rank semidefinite programming）</news:title>
   <news:publication_date>2026-07-25T10:39:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715745</loc>
  <lastmod>2026-07-25T10:38:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>風刺見出しの逆解析（Reverse-Engineering Satire, or &amp;quot;Paper on Computational Humor Accepted despite Making Serious Advances&amp;quot;）</news:title>
   <news:publication_date>2026-07-25T10:38:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715743</loc>
  <lastmod>2026-07-25T10:38:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Super-Kamiokande IVにおけるイベント再構成改良を伴う大気ニュートリノ振動解析（Atmospheric Neutrino Oscillation Analysis With Improved Event Reconstruction in Super-Kamiokande IV）</news:title>
   <news:publication_date>2026-07-25T10:38:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715741</loc>
  <lastmod>2026-07-25T10:38:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメトリック駆動散逸相転移を用いた量子トランスデューサ (A quantum transducer using a parametric driven-dissipative phase transition)</news:title>
   <news:publication_date>2026-07-25T10:38:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715739</loc>
  <lastmod>2026-07-25T09:47:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最大平均差の閉形式解とWasserstein Auto-Encoderへの応用（Closed-form Expressions for Maximum Mean Discrepancy with Applications to Wasserstein Auto-Encoders）</news:title>
   <news:publication_date>2026-07-25T09:47:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715737</loc>
  <lastmod>2026-07-25T09:46:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説明可能なベイズ決定木アルゴリズム（An Explainable Bayesian Decision Tree Algorithm）</news:title>
   <news:publication_date>2026-07-25T09:46:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715735</loc>
  <lastmod>2026-07-25T09:46:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Variable Importance Clouds（Variable Importance Clouds: A Way to Explore Variable Importance for the Set of Good Models）</news:title>
   <news:publication_date>2026-07-25T09:46:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715733</loc>
  <lastmod>2026-07-25T09:46:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的物体を扱う強化学習における運動知覚の重要性（Motion Perception in Reinforcement Learning with Dynamic Objects）</news:title>
   <news:publication_date>2026-07-25T09:46:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715731</loc>
  <lastmod>2026-07-25T09:45:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サーバーレス実行環境を用いた大規模最適化の活用（Harnessing the Power of Serverless Runtimes for Large-Scale Optimization）</news:title>
   <news:publication_date>2026-07-25T09:45:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715729</loc>
  <lastmod>2026-07-25T09:45:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>糖尿病予測に機械学習を使うという現実（Diabetes Prediction Using Machine Learning）</news:title>
   <news:publication_date>2026-07-25T09:45:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715727</loc>
  <lastmod>2026-07-25T09:45:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手術用パターン切開のための深層強化学習に基づく張力付与法（A New Tensioning Method using Deep Reinforcement Learning for Surgical Pattern Cutting）</news:title>
   <news:publication_date>2026-07-25T09:45:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715725</loc>
  <lastmod>2026-07-25T08:54:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コサイン類似度ペナルティによる弱教師あり音響イベント検出の識別強化（Cosine-similarity penalty to discriminate sound classes in weakly-supervised sound event detection）</news:title>
   <news:publication_date>2026-07-25T08:54:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715723</loc>
  <lastmod>2026-07-25T08:54:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストから感情を読み解く：データ駆動型モデルの実践と限界（Emotion Detection using Data Driven Models）</news:title>
   <news:publication_date>2026-07-25T08:54:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715721</loc>
  <lastmod>2026-07-25T08:53:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特許の先行技術検索を全文類似度で自動化する手法（Automating the search for a patent’s prior art with a full text similarity search）</news:title>
   <news:publication_date>2026-07-25T08:53:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715719</loc>
  <lastmod>2026-07-25T08:52:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UK Biobankを用いた両心室機能の自動大規模参照範囲算出（High Throughput Computation of Reference Ranges of Biventricular Cardiac Function on the UK Biobank Population Cohort）</news:title>
   <news:publication_date>2026-07-25T08:52:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715717</loc>
  <lastmod>2026-07-25T08:52:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形作用素による不等式制約を持つガウス過程（Gaussian Processes with Linear Operator Inequality Constraints）</news:title>
   <news:publication_date>2026-07-25T08:52:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715715</loc>
  <lastmod>2026-07-25T08:52:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル機械翻訳におけるジェンダーバイアス是正（Equalizing Gender Bias in Neural Machine Translation with Word Embeddings Techniques）</news:title>
   <news:publication_date>2026-07-25T08:52:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715713</loc>
  <lastmod>2026-07-25T08:51:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二つのワンクラス分類器による能動学習（Active Learning for One-Class Classification Using Two One-Class Classifiers）</news:title>
   <news:publication_date>2026-07-25T08:51:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715711</loc>
  <lastmod>2026-07-25T08:00:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>符号付きネットワークのクラスタリングに対するMBOスキーム導入（An MBO scheme for clustering and semi-supervised clustering of signed networks）</news:title>
   <news:publication_date>2026-07-25T08:00:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715709</loc>
  <lastmod>2026-07-25T08:00:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GM-PLLによる部分ラベル学習の刷新（GM-PLL: Graph Matching based Partial Label Learning）</news:title>
   <news:publication_date>2026-07-25T08:00:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715707</loc>
  <lastmod>2026-07-25T07:59:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速GPU対応の色正規化：病理スライド画像向け手法の実装改善（FAST GPU-ENABLED COLOR NORMALIZATION FOR DIGITAL PATHOLOGY）</news:title>
   <news:publication_date>2026-07-25T07:59:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715705</loc>
  <lastmod>2026-07-25T07:59:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層近傍識別ハッシングによる単一/複数ラベル画像検索の統一（Hierarchy Neighborhood Discriminative Hashing for An Unified View of Single-Label and Multi-Label Image retrieval）</news:title>
   <news:publication_date>2026-07-25T07:59:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715703</loc>
  <lastmod>2026-07-25T07:59:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像からの社会関係認識におけるマルチグラニュラリティ推論（MULTI-GRANULARITY REASONING FOR SOCIAL RELATION RECOGNITION FROM IMAGES）</news:title>
   <news:publication_date>2026-07-25T07:59:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715701</loc>
  <lastmod>2026-07-25T07:59:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>通信効率化のための量子化エポックSGD（Quantized Epoch-SGD）</news:title>
   <news:publication_date>2026-07-25T07:59:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715699</loc>
  <lastmod>2026-07-25T07:58:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像変換によるニューラルネットワークの敵対的サンプル耐性向上（Image Transformation can make Neural Networks more robust against Adversarial Examples）</news:title>
   <news:publication_date>2026-07-25T07:58:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715697</loc>
  <lastmod>2026-07-25T07:08:07Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-25T07:08:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <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>
  <loc>https://aibr.jp/archives/715693</loc>
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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:publication_date>2026-07-25T07:07:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-07-25T07:07:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-25T07:06:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715687</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-25T07:06:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-25T07:06:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715683</loc>
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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:publication_date>2026-07-25T06:15:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715681</loc>
  <lastmod>2026-07-25T06:15:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的ニューラルアーキテクチャ探索によるセマンティック画像セグメンテーション（Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation）</news:title>
   <news:publication_date>2026-07-25T06:15:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715679</loc>
  <lastmod>2026-07-25T06:15:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の感情認識のための深層学習（Deep Learning for Human Affect Recognition: Insights and New Developments）</news:title>
   <news:publication_date>2026-07-25T06:15:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715677</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>スティグメルギーを計算記憶として利用するRNN設計（Using stigmergy as a computational memory in the design of recurrent neural networks）</news:title>
   <news:publication_date>2026-07-25T06:14:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715675</loc>
  <lastmod>2026-07-25T06:14:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>携帯通信データとネットワーク構造から人口属性を推定する手法（Inference of Demographic Attributes based on Mobile Phone Usage Patterns and Social Network Topology）</news:title>
   <news:publication_date>2026-07-25T06:14:12Z</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>アルゴリズム的ベイズ群選択（Algorithmic Bayesian Group Gibbs Selection）</news:title>
   <news:publication_date>2026-07-25T06:13:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/715671</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>パーツ単位の3D形状モデリングと潜在空間分解（Composite Shape Modeling via Latent Space Factorization）</news:title>
   <news:publication_date>2026-07-25T06:13:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715669</loc>
  <lastmod>2026-07-25T05:23:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EMアルゴリズムを超えて：潜在クラスモデルの拘束付き最適化手法 (Beyond the EM Algorithm: Constrained Optimization Methods for Latent Class Model)</news:title>
   <news:publication_date>2026-07-25T05:23:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715667</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>塩ドーム境界追跡のためのテンソルベース部分空間学習（Tensor-based Subspace Learning for Tracking Salt-Dome Boundaries）</news:title>
   <news:publication_date>2026-07-25T05:22:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715665</loc>
  <lastmod>2026-07-25T05:22:24Z</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で画素単位の理解を導くTraceCaps（TraceCaps: A Capsule-based Neural Network for Semantic Segmentation）</news:title>
   <news:publication_date>2026-07-25T05:22:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715663</loc>
  <lastmod>2026-07-25T05:21:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模集団における適応学習（Adaptive Learning in Large Populations）</news:title>
   <news:publication_date>2026-07-25T05:21:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/715661</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>人間行動から明らかになる解釈可能な物体表現（Revealing Interpretable Object Representations from Human Behavior）</news:title>
   <news:publication_date>2026-07-25T05:21:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715659</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>ハイパーキューブに基づく位相カバリングを用いたニューラルネットワークのワンショット構築（A Constructive Approach for One-Shot Training of Neural Networks Using Hypercube-Based Topological Coverings）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715657</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>3D形状プログラムの学習と実行（LEARNING TO INFER AND EXECUTE 3D SHAPE PROGRAMS）</news:title>
   <news:publication_date>2026-07-25T04:29:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715655</loc>
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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>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715653</loc>
  <lastmod>2026-07-25T04:29:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Transformer-XL: 固定長コンテキストを越える注意型言語モデル (Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context)</news:title>
   <news:publication_date>2026-07-25T04:29:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715651</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>屋内マルチモーダル人間活動認識データセット（LboroHAR: A Multimodal Sensor Dataset for Human Activity Recognition）</news:title>
   <news:publication_date>2026-07-25T04:28:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715649</loc>
  <lastmod>2026-07-25T04:27:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Learnable Manifold Alignment（Learnable Manifold Alignment (LeMA) : A Semi-supervised Cross-modality Learning Framework for Land Cover and Land Use Classification）</news:title>
   <news:publication_date>2026-07-25T04:27:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715647</loc>
  <lastmod>2026-07-25T04:27:40Z</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>2026-07-25T04:27:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715645</loc>
  <lastmod>2026-07-25T04:27:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>キラル・アイソスピン不均衡下の濃縮クォーク物質における双対性と非一様相（Dualities and inhomogeneous phases in dense quark matter with chiral and isospin imbalances）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715643</loc>
  <lastmod>2026-07-25T03:36:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光音響イメージングで脳内の広がる脱分極を可視化する（Photoacoustics can image spreading depolarization deep in gyrencephalic brain）</news:title>
   <news:publication_date>2026-07-25T03:36:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715641</loc>
  <lastmod>2026-07-25T03:35:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層生成モデルの過学習検出手法の実装と示唆（Detecting Overﬁtting of Deep Generative Networks via Latent Recovery）</news:title>
   <news:publication_date>2026-07-25T03:35:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715639</loc>
  <lastmod>2026-07-25T03:35:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光学格子中ディポールボースの平均場越え補正（Beyond-mean-field corrections for dipolar bosons in an optical lattice）</news:title>
   <news:publication_date>2026-07-25T03:35:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715637</loc>
  <lastmod>2026-07-25T03:34:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互コヒーレンスを用いたℓ1/ℓ0同等性の証明と分類問題への示唆（The Use of Mutual Coherence to Prove ℓ1/ℓ0-Equivalence in Classification Problems）</news:title>
   <news:publication_date>2026-07-25T03:34:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715635</loc>
  <lastmod>2026-07-25T03:34:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Newtonハードスレッショルディングパースートの全域的かつ二次収束（Global and Quadratic Convergence of Newton Hard-Thresholding Pursuit）</news:title>
   <news:publication_date>2026-07-25T03:34:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715633</loc>
  <lastmod>2026-07-25T03:34:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チェコ語テキストの感情分析のアルゴリズム的概観（Sentiment Analysis of Czech Texts: An Algorithmic Survey）</news:title>
   <news:publication_date>2026-07-25T03:34:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715631</loc>
  <lastmod>2026-07-25T03:34:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層別プルーニングによる表現のコンパクトさ評価（How Compact?: Assessing Compactness of Representations through Layer-Wise Pruning）</news:title>
   <news:publication_date>2026-07-25T03:34:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715629</loc>
  <lastmod>2026-07-25T02:42:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散意思決定のためのエージェントベースモデル（Agent-Based Modelling Approach for Distributed Decision Support in an IoT Network）</news:title>
   <news:publication_date>2026-07-25T02:42:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715627</loc>
  <lastmod>2026-07-25T02:33:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グレーピクセルの検出と照明推定（On Finding Gray Pixels）</news:title>
   <news:publication_date>2026-07-25T02:33:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715625</loc>
  <lastmod>2026-07-25T02:32:46Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディリクレ変分オートエンコーダ（DIRICHLET VARIATIONAL AUTOENCODER）</news:title>
   <news:publication_date>2026-07-25T02:32:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/715623</loc>
  <lastmod>2026-07-25T02:31:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>茶葉画像に基づく病害識別のCNN応用（Image Recognition of Tea Leaf Diseases Based on Convolutional Neural Network）</news:title>
   <news:publication_date>2026-07-25T02:31:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715621</loc>
  <lastmod>2026-07-25T02:31:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートフォンのスクリーンショットをクラスタリングする能動学習（Guess What’s on My Screen? Clustering Smartphone Screenshots with Active Learning）</news:title>
   <news:publication_date>2026-07-25T02:31:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715619</loc>
  <lastmod>2026-07-25T02:30:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TSKファジィシステムによる転移表現学習の提案（Transfer Representation Learning with TSK-FS）</news:title>
   <news:publication_date>2026-07-25T02:30:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715617</loc>
  <lastmod>2026-07-25T02:30:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プログラミング科目における学生成績予測のためのモバイル連携機械学習モデル開発 (Development of Mobile-Interfaced Machine Learning-Based Predictive Models for Improving Students’ Performance in Programming Courses)</news:title>
   <news:publication_date>2026-07-25T02:30:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715615</loc>
  <lastmod>2026-07-25T01:39:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層意味マルチモーダルハッシングネットワーク（Deep Semantic Multimodal Hashing Network for Scalable Image-Text and Video-Text Retrievals）</news:title>
   <news:publication_date>2026-07-25T01:39:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715613</loc>
  <lastmod>2026-07-25T01:31:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統計的ミンコフスキー距離の閉形式解（The statistical Minkowski distances: Closed-form formula for Gaussian Mixture Models）</news:title>
   <news:publication_date>2026-07-25T01:31:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715611</loc>
  <lastmod>2026-07-25T01:31:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔関連タスクの低コスト転移学習（Low-Cost Transfer Learning of Face Tasks）</news:title>
   <news:publication_date>2026-07-25T01:31:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715609</loc>
  <lastmod>2026-07-25T01:30:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>活性化関数をめぐる大規模比較――NLPタスクで見えた安定性の本命（Is it Time to Swish? Comparing Deep Learning Activation Functions Across NLP tasks）</news:title>
   <news:publication_date>2026-07-25T01:30:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715607</loc>
  <lastmod>2026-07-25T01:29:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>透明な誘電体内でのレーザーパルス誘起ブレークダウンに伴うサブ波長周期プラズマ構造（Subwavelength periodic plasma structures formed during the laser-pulse-induced breakdown within the transparent dielectric）</news:title>
   <news:publication_date>2026-07-25T01:29:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715605</loc>
  <lastmod>2026-07-25T01:29:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>S波重クォークニウムの排他的電磁生成に関する理論的不確かさ（Theoretical uncertainties in exclusive electroproduction of S-wave heavy quarkonia）</news:title>
   <news:publication_date>2026-07-25T01:29:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715603</loc>
  <lastmod>2026-07-25T01:29:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワイヤレス通信における動的システムのための人工知能（Artificial Intelligence for Dynamical Systems in Wireless Communications: Modeling for the Future）</news:title>
   <news:publication_date>2026-07-25T01:29:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715601</loc>
  <lastmod>2026-07-25T00:38:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語表現は何を表しているのか（What do Language Representations Really Represent?）</news:title>
   <news:publication_date>2026-07-25T00:38:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715599</loc>
  <lastmod>2026-07-25T00:37:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱く位置合わせされたクロスモーダル学習による多波長歩行者検出 (Weakly Aligned Cross-Modal Learning for Multispectral Pedestrian Detection)</news:title>
   <news:publication_date>2026-07-25T00:37:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715597</loc>
  <lastmod>2026-07-25T00:37:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生物学に着想を得た視覚ワーキングメモリとその意味（A Biologically Inspired Visual Working Memory for Deep Networks）</news:title>
   <news:publication_date>2026-07-25T00:37:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715595</loc>
  <lastmod>2026-07-25T00:36:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Humanoid: 人間の操作を学ぶことでGUIテストを賢くする（Humanoid: A Deep Learning-based Approach to Automated Black-box Android App Testing）</news:title>
   <news:publication_date>2026-07-25T00:36:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715593</loc>
  <lastmod>2026-07-25T00:36:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速CNNベースの物体追跡と局所化層による特徴補間（Fast CNN-Based Object Tracking Using Localization Layers and Deep Features Interpolation）</news:title>
   <news:publication_date>2026-07-25T00:36:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715591</loc>
  <lastmod>2026-07-25T00:35:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UAV操作とジェスチャー認識のためのデータセット（UAV-GESTURE: A Dataset for UAV Control and Gesture Recognition）</news:title>
   <news:publication_date>2026-07-25T00:35:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715589</loc>
  <lastmod>2026-07-25T00:35:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形逆散乱問題に対する深層畳み込みニューラルネットワークの性能解析と動的挙動（Performance Analysis and Dynamic Evolution of Deep Convolutional Neural Network for Nonlinear Inverse Scattering）</news:title>
   <news:publication_date>2026-07-25T00:35:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715587</loc>
  <lastmod>2026-07-24T23:43:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変動する重力定数におけるガウスの法則とポアソン方程式の源（Gauss’s Law and the Source for Poisson’s Equation in Modified Gravity with Varying G）</news:title>
   <news:publication_date>2026-07-24T23:43:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715585</loc>
  <lastmod>2026-07-24T23:43:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間変化を考慮した建物パラメータ推定と事前知識の導入（Estimating Buildings’ Parameters over Time Including Prior Knowledge）</news:title>
   <news:publication_date>2026-07-24T23:43:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715583</loc>
  <lastmod>2026-07-24T23:42:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個体識別のためのフィン画像埋め込み学習（Individual common dolphin identification via metric embedding learning）</news:title>
   <news:publication_date>2026-07-24T23:42:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715581</loc>
  <lastmod>2026-07-24T23:42:31Z</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>2026-07-24T23:42:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715579</loc>
  <lastmod>2026-07-24T23:42:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化データの高忠実度ベクトル空間モデル（High-Fidelity Vector Space Models of Structured Data）</news:title>
   <news:publication_date>2026-07-24T23:42:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715577</loc>
  <lastmod>2026-07-24T23:41:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファイアフライアルゴリズムによるソフトウェア工数見積り最適化（Optimizing Software Effort Estimation Models Using Firefly Algorithm）</news:title>
   <news:publication_date>2026-07-24T23:41:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715575</loc>
  <lastmod>2026-07-24T23:41:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル不確実性下の堅牢かつ適応的な計画（Robust and Adaptive Planning under Model Uncertainty）</news:title>
   <news:publication_date>2026-07-24T23:41:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715573</loc>
  <lastmod>2026-07-24T22:50:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プールを超えて訓練画像を作る：相対属性のための能動的画像生成（Thinking Outside the Pool: Active Training Image Creation for Relative Attributes）</news:title>
   <news:publication_date>2026-07-24T22:50:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715571</loc>
  <lastmod>2026-07-24T22:50:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>油層内流動を予測する深層ニューラルネットワーク（DEEP NEURAL NETWORKS PREDICTING OIL MOVEMENT IN A DEVELOPMENT UNIT）</news:title>
   <news:publication_date>2026-07-24T22:50:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715569</loc>
  <lastmod>2026-07-24T22:39:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>製品情報質問応答のための教師あり転移学習（Supervised Transfer Learning for Product Information Question Answering）</news:title>
   <news:publication_date>2026-07-24T22:39:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715567</loc>
  <lastmod>2026-07-24T22:38:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡な時系列分類に対するGANとオートエンコーダの統合（Autoencoders and Generative Adversarial Networks for Imbalanced Sequence Classification）</news:title>
   <news:publication_date>2026-07-24T22:38:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715565</loc>
  <lastmod>2026-07-24T22:38:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロバストな変化記述（Robust Change Captioning）</news:title>
   <news:publication_date>2026-07-24T22:38:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715563</loc>
  <lastmod>2026-07-24T22:38:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コミュニティ検出のEXIT解析 (EXIT Analysis for Community Detection)</news:title>
   <news:publication_date>2026-07-24T22:38:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715561</loc>
  <lastmod>2026-07-24T22:37:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTデバイス上での深層ニューラルネットワークの協調実行（Collaborative Execution of Deep Neural Networks on Internet of Things Devices）</news:title>
   <news:publication_date>2026-07-24T22:37:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715559</loc>
  <lastmod>2026-07-24T21:46:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転におけるマルチストリームCNNベースの動画意味セグメンテーション (Multi-stream CNN based Video Semantic Segmentation for Automated Driving)</news:title>
   <news:publication_date>2026-07-24T21:46:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715557</loc>
  <lastmod>2026-07-24T21:46:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マニホールド学習を用いたグローバル形状記述子の応用（An Application of Manifold Learning in Global Shape Descriptors）</news:title>
   <news:publication_date>2026-07-24T21:46:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715555</loc>
  <lastmod>2026-07-24T21:46:08Z</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/715553</loc>
  <lastmod>2026-07-24T21:45:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適切な単語選択を支援する双方向LSTMタグ付け器の応用（Choosing the Right Word: Using Bidirectional LSTM Tagger for Writing Support Systems）</news:title>
   <news:publication_date>2026-07-24T21:45:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715551</loc>
  <lastmod>2026-07-24T21:45:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的新奇性と好奇心がもたらす学習加速（Visual novelty, curiosity, and intrinsic reward in machine learning and the brain）</news:title>
   <news:publication_date>2026-07-24T21:45:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715549</loc>
  <lastmod>2026-07-24T21:44:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>熱帯カエル群集の音声記録における出現-非出現推定（Presence-absence estimation in audio recordings of tropical frog communities）</news:title>
   <news:publication_date>2026-07-24T21:44:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715547</loc>
  <lastmod>2026-07-24T21:44:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FDD Massive MIMOにおけるダウンリンクCSI予測を実現する深層学習（Enabling FDD Massive MIMO through Deep Learning-based Channel Prediction）</news:title>
   <news:publication_date>2026-07-24T21:44:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715545</loc>
  <lastmod>2026-07-24T20:53:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランク構造を持つ双線形バンディット（Bilinear Bandits with Low-rank Structure）</news:title>
   <news:publication_date>2026-07-24T20:53:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715543</loc>
  <lastmod>2026-07-24T20:52:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列・連続値・離散値を扱う差分プライバシー付きGANの応用（Differentially Private Generative Adversarial Networks for Time Series, Continuous, and Discrete Open Data）</news:title>
   <news:publication_date>2026-07-24T20:52:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715541</loc>
  <lastmod>2026-07-24T20:52:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>あいまいビットとニューラルネットワークによるハッシュ関数部分逆演（Using fuzzy bits and neural networks to partially invert few rounds of some cryptographic hash functions）</news:title>
   <news:publication_date>2026-07-24T20:52:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715539</loc>
  <lastmod>2026-07-24T20:52:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相対論的f-ダイバージェンスの理論と実務的示唆 (On Relativistic f-Divergences)</news:title>
   <news:publication_date>2026-07-24T20:52:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715537</loc>
  <lastmod>2026-07-24T20:52:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画における未見物体のセグメンテーション（Unseen Object Segmentation in Videos via Transferable Representations）</news:title>
   <news:publication_date>2026-07-24T20:52:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715535</loc>
  <lastmod>2026-07-24T20:51:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長ガンマ線バースト（LGRB）は星形成を正しく追えるか（Are LGRBs biased tracers of star formation? Clues from the BAT6 sample）</news:title>
   <news:publication_date>2026-07-24T20:51:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715533</loc>
  <lastmod>2026-07-24T20:51:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホップフィールドネットワークの連想記憶を模擬する量子確率的ウォークの実験的実装（Experimental quantum stochastic walks simulating associative memory of Hopfield neural networks）</news:title>
   <news:publication_date>2026-07-24T20:51:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715531</loc>
  <lastmod>2026-07-24T20:00:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リッチで深い監督による顕著物体検出の改良 (Richer and Deeper Supervision Network for Salient Object Detection)</news:title>
   <news:publication_date>2026-07-24T20:00:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715529</loc>
  <lastmod>2026-07-24T20:00:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反射による協調型ニューラルネットワーク群の学習（Learning with Collaborative Neural Network Group by Reflection）</news:title>
   <news:publication_date>2026-07-24T20:00:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715527</loc>
  <lastmod>2026-07-24T20:00:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スイッチングガウス過程モデルによる不確実性定量を伴う適応的活動モニタリング (Adaptive Activity Monitoring with Uncertainty Quantification in Switching Gaussian Process Models)</news:title>
   <news:publication_date>2026-07-24T20:00:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715525</loc>
  <lastmod>2026-07-24T19:59:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子工学のモデルベース推論を考察するためのシンクアラウド面接法（Using think-aloud interviews to characterize model-based reasoning in electronics for a laboratory course assessment）</news:title>
   <news:publication_date>2026-07-24T19:59:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715523</loc>
  <lastmod>2026-07-24T19:59:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スピントロニクスを用いた再構成可能なニューロモルフィック配列（SNRA: A Spintronic Neuromorphic Reconfigurable Array for In-Circuit Training and Evaluation of Deep Belief Networks）</news:title>
   <news:publication_date>2026-07-24T19:59:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715521</loc>
  <lastmod>2026-07-24T19:59:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像から室内シーンを逆レンダリングするニューラル手法（Neural Inverse Rendering of an Indoor Scene from a Single Image）</news:title>
   <news:publication_date>2026-07-24T19:59:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715519</loc>
  <lastmod>2026-07-24T19:58:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体分類における解釈可能なCNN（Interpretable CNNs for Object Classification）</news:title>
   <news:publication_date>2026-07-24T19:58:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715517</loc>
  <lastmod>2026-07-24T19:07:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔認識システムの構築と課題（Face Recognition System）</news:title>
   <news:publication_date>2026-07-24T19:07:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715515</loc>
  <lastmod>2026-07-24T19:06:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチパーティ機械学習における汚染攻撃とその緩和（Contamination Attacks and Mitigation in Multi-Party Machine Learning）</news:title>
   <news:publication_date>2026-07-24T19:06:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715513</loc>
  <lastmod>2026-07-24T19:06:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長文からの画像生成（GILT: Generating Images from Long Text）</news:title>
   <news:publication_date>2026-07-24T19:06:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715511</loc>
  <lastmod>2026-07-24T19:05:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ダイカストにおける凝固最適化（Optimization of Solidification in Die Casting using Numerical Simulations and Machine Learning）</news:title>
   <news:publication_date>2026-07-24T19:05:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715509</loc>
  <lastmod>2026-07-24T19:05:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>古典データを量子重ね合わせへ書き込む回路設計（Circuit-Based Quantum Random Access Memory for Classical Data）</news:title>
   <news:publication_date>2026-07-24T19:05:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715507</loc>
  <lastmod>2026-07-24T19:04:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフィカルモデル推論：確率的サンプリングと決定論的近似の融合（Graphical model inference: Sequential Monte Carlo meets deterministic approximations）</news:title>
   <news:publication_date>2026-07-24T19:04:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715505</loc>
  <lastmod>2026-07-24T19:04:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタリングにおける公平なアルゴリズム（Fair Algorithms for Clustering）</news:title>
   <news:publication_date>2026-07-24T19:04:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715503</loc>
  <lastmod>2026-07-24T18:12:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FastGRNN: 極小かつ高精度なRNNでエッジ推論を現実にする（FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network）</news:title>
   <news:publication_date>2026-07-24T18:12:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715501</loc>
  <lastmod>2026-07-24T18:12:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプル単位の学習しやすさを比較する研究（Comparing Sample-wise Learnability Across Deep Neural Network Models）</news:title>
   <news:publication_date>2026-07-24T18:12:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715499</loc>
  <lastmod>2026-07-24T18:12:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fenchel‑Young損失による学習の原理（Learning with Fenchel-Young Losses）</news:title>
   <news:publication_date>2026-07-24T18:12:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715497</loc>
  <lastmod>2026-07-24T18:10:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤差関数における引力盆地の可視化（Visualising Basins of Attraction for the Cross-Entropy and the Squared Error Neural Network Loss Functions）</news:title>
   <news:publication_date>2026-07-24T18:10:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715495</loc>
  <lastmod>2026-07-24T18:10:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>選択的メタモルフォーシスによる成長モデリング（Selective metamorphosis for growth modelling with applications to landmarks）</news:title>
   <news:publication_date>2026-07-24T18:10:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715493</loc>
  <lastmod>2026-07-24T18:10:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザー埋め込みを学習するための融合戦略（Fusion Strategies for Learning User Embeddings with Neural Networks）</news:title>
   <news:publication_date>2026-07-24T18:10:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715491</loc>
  <lastmod>2026-07-24T18:10:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ畳み込みニューラルネットワークと変分推論の包括的ガイド（A Comprehensive guide to Bayesian Convolutional Neural Network with Variational Inference）</news:title>
   <news:publication_date>2026-07-24T18:10:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715489</loc>
  <lastmod>2026-07-24T17:18:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対称ラベルノイズ下におけるコスト感度学習（Cost Sensitive Learning in the Presence of Symmetric Label Noise）</news:title>
   <news:publication_date>2026-07-24T17:18:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715487</loc>
  <lastmod>2026-07-24T17:17:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様な応答スタイルを一モデルで扱う生成型読解（Multi-Style Generative Reading Comprehension）</news:title>
   <news:publication_date>2026-07-24T17:17:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715485</loc>
  <lastmod>2026-07-24T17:16:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層自己符号化器のアンサンブルによるスペクトラルクラスタリング（Spectral Clustering via Ensemble Deep Autoencoder Learning）</news:title>
   <news:publication_date>2026-07-24T17:16:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715483</loc>
  <lastmod>2026-07-24T17:16:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Soft-Bayesによる専門家混合の確率予測（Soft-Bayes: Prod for Mixtures of Experts with Log-Loss）</news:title>
   <news:publication_date>2026-07-24T17:16:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715481</loc>
  <lastmod>2026-07-24T17:15:59Z</lastmod>
  <news:news>
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   <news:title>製造現場のOEEを予測して改善するAI手法（Artificial Intelligence and Machine Learning to Predict and Improve Efficiency in Manufacturing Industry）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>小さいバッチで多GPUを活かす仕組み（CROSSBOW: Scaling Deep Learning with Small Batch Sizes on Multi-GPU Servers）</news:title>
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    <news:language>ja</news:language>
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   <news:title>深層ニューラルネットワーク近似理論（Deep Neural Network Approximation Theory）</news:title>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>不確実性に基づく深層強化学習における外部分布検出（Uncertainty-Based Out-of-Distribution Detection in Deep Reinforcement Learning）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Tree Tensor Networksによる生成モデル（Tree Tensor Networks for Generative Modeling）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:title>不規則小惑星着陸のリアルタイム最適制御（Real-Time Optimal Control for Irregular Asteroid Landings Using Deep Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>SAR画像を光学画像へ翻訳して解釈を支援する手法（Translating SAR to Optical Images for Assisted Interpretation）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>少数ショットで画像を生み出すメタ学習（FIGR: Few-shot Image Generation with Reptile）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>生体信号で見破る偽動画検出（FakeCatcher: Detection of Synthetic Portrait Videos using Biological Signals）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>AlphaGoの意思決定を解く：ニューラルネットワークに埋め込まれた局所的な文脈効果の可視化（Explaining AlphaGo: Interpreting Contextual Effects in Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>StaBL：Webアプリケーション仕様のための状態ベース言語（StaBL - State Based Language for Specification of Web Applications）</news:title>
   <news:publication_date>2026-07-24T15:29:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>プライバシー保証付きデータマスキング (Data Masking with Privacy Guarantees)</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>太陽帆を用いた複数近地球小惑星探査の軌道設計（Solar-Sail Trajectory Design for Multiple Near-Earth Asteroid Exploration Based on Deep Neural Networks）</news:title>
   <news:publication_date>2026-07-24T15:28:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>リスク認識型アクティブ逆強化学習（Risk-Aware Active Inverse Reinforcement Learning）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-24T15:27:46Z</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>
  <loc>https://aibr.jp/archives/715449</loc>
  <lastmod>2026-07-24T15:27:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>RastaPLP特徴とSVMによる音声CAPTCHA認識（Audio Captcha Recognition Using RastaPLP Features by SVM）</news:title>
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   <news:genres>Blog</news:genres>
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