<?xml version="1.0" encoding="UTF-8"?>
<!--generator='jetpack-16.0-a.5'-->
<!--Jetpack_Sitemap_Buffer_News_XMLWriter-->
<?xml-stylesheet type="text/xsl" href="//aibr.jp/news-sitemap.xsl"?>
<urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9" xmlns:news="http://www.google.com/schemas/sitemap-news/0.9" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.sitemaps.org/schemas/sitemap/0.9 http://www.sitemaps.org/schemas/sitemap/0.9/sitemap.xsd">
 <url>
  <loc>https://aibr.jp/archives/706106</loc>
  <lastmod>2026-06-29T06:06:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PAC-Bayesian境界を最小化して学習するガウス過程（Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds）</news:title>
   <news:publication_date>2026-06-29T06:06:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706104</loc>
  <lastmod>2026-06-29T06:06:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低線量CT再構成を変える「画像マニフォールド」手法（Low dose CT reconstruction assisted by an image manifold prior）</news:title>
   <news:publication_date>2026-06-29T06:06:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706102</loc>
  <lastmod>2026-06-29T06:05:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MAESTROデータセットによるピアノ音楽生成の革新（Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset）</news:title>
   <news:publication_date>2026-06-29T06:05:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706100</loc>
  <lastmod>2026-06-29T06:05:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数ショットで挑む3D多モーダル医用画像分割（Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning）</news:title>
   <news:publication_date>2026-06-29T06:05:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706098</loc>
  <lastmod>2026-06-29T06:05:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習によるGMsFEM離散化の予測（Prediction of Discretization of GMsFEM using Deep Learning）</news:title>
   <news:publication_date>2026-06-29T06:05:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706096</loc>
  <lastmod>2026-06-29T06:04:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類と適応提案を組み合わせた近似ベイズ推論（Approximate Bayesian Computation via Population Monte Carlo and Classification）</news:title>
   <news:publication_date>2026-06-29T06:04:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706094</loc>
  <lastmod>2026-06-29T06:04:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ支援型構造故障同定（Data-assisted structural fault identification）</news:title>
   <news:publication_date>2026-06-29T06:04:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706092</loc>
  <lastmod>2026-06-29T05:13:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習ハイパーヒューリスティックによるマルチ目的最適化の単点探索応用（A Reinforcement Learning Hyper‑Heuristic in Multi‑Objective Single Point Search）</news:title>
   <news:publication_date>2026-06-29T05:13:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706090</loc>
  <lastmod>2026-06-29T05:13:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>夢を見るニューラルネットワーク：不要な記憶の忘却と重要な記憶の強化（Dreaming neural networks: forgetting spurious memories and reinforcing pure ones）</news:title>
   <news:publication_date>2026-06-29T05:13:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706088</loc>
  <lastmod>2026-06-29T05:13:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習が明かす宇宙の新情報（Machine learning uncovers new cosmological information）</news:title>
   <news:publication_date>2026-06-29T05:13:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706086</loc>
  <lastmod>2026-06-29T05:12:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Learning as a Serviceフレームワーク比較測定研究（A Comparative Measurement Study of Deep Learning as a Service Framework）</news:title>
   <news:publication_date>2026-06-29T05:12:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706084</loc>
  <lastmod>2026-06-29T05:12:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的バンディットに対する報酬操作攻撃（Adversarial Attacks on Stochastic Bandits）</news:title>
   <news:publication_date>2026-06-29T05:12:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706082</loc>
  <lastmod>2026-06-29T05:12:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReviewQA—関係性に基づくアスペクト別意見読解データセット (ReviewQA: a relational aspect-based opinion reading dataset)</news:title>
   <news:publication_date>2026-06-29T05:12:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706080</loc>
  <lastmod>2026-06-29T05:12:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピラミッド型Person Re-IDと動的マルチロス学習（Pyramidal Person Re-Identification via Multi-Loss Dynamic Training）</news:title>
   <news:publication_date>2026-06-29T05:12:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706078</loc>
  <lastmod>2026-06-29T04:21:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepSphere：HEALPixサンプリングを用いた効率的球面畳み込みニューラルネットワーク（DeepSphere: Efficient spherical Convolutional Neural Network with HEALPix sampling for cosmological applications）</news:title>
   <news:publication_date>2026-06-29T04:21:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706076</loc>
  <lastmod>2026-06-29T04:21:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波形ドメインでのエンドツーエンド音楽源分離は可能か（End-to-end music source separation: is it possible in the waveform domain?）</news:title>
   <news:publication_date>2026-06-29T04:21:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706074</loc>
  <lastmod>2026-06-29T04:21:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓MRIの動きによるアーチファクトを自動検出するCNN手法（Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning）</news:title>
   <news:publication_date>2026-06-29T04:21:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706072</loc>
  <lastmod>2026-06-29T04:20:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声と表情を同時に変換する技術の要点（Audiovisual Speaker Conversion: Jointly and Simultaneously Transforming Facial Expression and Acoustic Characteristics）</news:title>
   <news:publication_date>2026-06-29T04:20:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706070</loc>
  <lastmod>2026-06-29T04:19:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆問題のためのマルチスケール畳み込みニューラルネットワーク (Multi-scale Convolutional Neural Networks for Inverse Problems)</news:title>
   <news:publication_date>2026-06-29T04:19:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706068</loc>
  <lastmod>2026-06-29T04:19:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師なし学習による人間行動推定（Semi-unsupervised Learning of Human Activity using Deep Generative Models）</news:title>
   <news:publication_date>2026-06-29T04:19:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706066</loc>
  <lastmod>2026-06-29T04:19:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンピュータモデルの変分較正（Variational Calibration of Computer Models）</news:title>
   <news:publication_date>2026-06-29T04:19:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706064</loc>
  <lastmod>2026-06-29T03:28:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈を意識した音声認識における『難しいネガティブ例』を使った学習（Contextual Speech Recognition with Difficult Negative Training Examples）</news:title>
   <news:publication_date>2026-06-29T03:28:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706062</loc>
  <lastmod>2026-06-29T03:27:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲノムとメタゲノムの相互作用を高速に解析する手法（Fast Computation of Genome-Metagenome Interaction Effects）</news:title>
   <news:publication_date>2026-06-29T03:27:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706060</loc>
  <lastmod>2026-06-29T03:27:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフニューラルネットワークにおける中央値活性化関数（MEDIAN ACTIVATION FUNCTIONS FOR GRAPH NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-06-29T03:27:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706058</loc>
  <lastmod>2026-06-29T03:26:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルベース能動探索（Model-Based Active eXploration）</news:title>
   <news:publication_date>2026-06-29T03:26:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706056</loc>
  <lastmod>2026-06-29T03:26:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低複雑度RNNを用いた極性符号デコーダと重み量子化の実践的解説（LOW-COMPLEXITY RECURRENT NEURAL NETWORK-BASED POLAR DECODER WITH WEIGHT QUANTIZATION MECHANISM）</news:title>
   <news:publication_date>2026-06-29T03:26:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706054</loc>
  <lastmod>2026-06-29T03:26:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波ネットワークによる無向グラフでの長距離情報学習（Deep learning long-range information in undirected graphs with wave networks）</news:title>
   <news:publication_date>2026-06-29T03:26:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706052</loc>
  <lastmod>2026-06-29T03:26:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正則化付き最尤推定による混合エキスパートモデルの変革（Regularized Maximum Likelihood Estimation and Feature Selection in Mixtures-of-Experts Models）</news:title>
   <news:publication_date>2026-06-29T03:26:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706050</loc>
  <lastmod>2026-06-29T02:35:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同時ワイヤレス情報・電力伝送を学習で設計する（A Learning Approach to Wireless Information and Power Transfer）</news:title>
   <news:publication_date>2026-06-29T02:35:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706048</loc>
  <lastmod>2026-06-29T02:34:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イメージに基づくサンプル構築によるゼロショット学習（Imagination Based Sample Construction for Zero-Shot Learning）</news:title>
   <news:publication_date>2026-06-29T02:34:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706046</loc>
  <lastmod>2026-06-29T02:34:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークによる音楽のオーディオ・インペインティング（AUDIO INPAINTING OF MUSIC BY MEANS OF NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-06-29T02:34:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706044</loc>
  <lastmod>2026-06-29T02:34:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子層堆積による高アスペクト比イリジウムX線回折格子の作製（Towards Sub-micrometer High Aspect Ratio X-ray Gratings by Atomic Layer Deposition of Iridium）</news:title>
   <news:publication_date>2026-06-29T02:34:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706042</loc>
  <lastmod>2026-06-29T02:33:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>段階的機械学習によるエンティティ解決（Gradual Machine Learning for Entity Resolution）</news:title>
   <news:publication_date>2026-06-29T02:33:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706040</loc>
  <lastmod>2026-06-29T02:33:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相ハーモニック相関と畳み込みニューラルネットワーク（Phase Harmonic Correlations and Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-29T02:33:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706038</loc>
  <lastmod>2026-06-29T02:33:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バースト画像の自動選別で画質を最大化する手法（Burst ranking for blind multi-image deblurring）</news:title>
   <news:publication_date>2026-06-29T02:33:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706036</loc>
  <lastmod>2026-06-29T01:41:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遺伝子発現から薬物応答を予測する協調フィルタリング手法（FROM GENE EXPRESSION TO DRUG RESPONSE: A COLLABORATIVE FILTERING APPROACH）</news:title>
   <news:publication_date>2026-06-29T01:41:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706034</loc>
  <lastmod>2026-06-29T01:40:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動車精密部品の欠陥検出を統合した深層ネットワーク（PartsNet: A Unified Deep Network for Automotive Engine Precision Parts Defect Detection）</news:title>
   <news:publication_date>2026-06-29T01:40:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706032</loc>
  <lastmod>2026-06-29T01:32:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理学研究の進化を予測する機械学習（Using Machine Learning to Predict the Evolution of Physics Research）</news:title>
   <news:publication_date>2026-06-29T01:32:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706030</loc>
  <lastmod>2026-06-29T01:32:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的損失関数で学ぶ「教えること」の自動化（Learning to Teach with Dynamic Loss Functions）</news:title>
   <news:publication_date>2026-06-29T01:32:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706028</loc>
  <lastmod>2026-06-29T01:31:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰型ニューラルネットワークの訓練収束率に関する理論的進展（On the Convergence Rate of Training Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-06-29T01:31:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706026</loc>
  <lastmod>2026-06-29T01:30:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構付きSeq2Seqモデルによる音声合成の話し方スタイル適応（SPEAKING STYLE ADAPTATION IN TEXT-TO-SPEECH SYNTHESIS USING SEQUENCE-TO-SEQUENCE MODELS WITH ATTENTION）</news:title>
   <news:publication_date>2026-06-29T01:30:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706024</loc>
  <lastmod>2026-06-29T01:30:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続学習における「条件付きリプレイ」と「周辺（マージナル）リプレイ」の比較（Marginal Replay vs Conditional Replay for Continual Learning）</news:title>
   <news:publication_date>2026-06-29T01:30:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706022</loc>
  <lastmod>2026-06-29T00:39:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パッチベースのスパース表現による細菌検出（PATCH-BASED SPARSE REPRESENTATION FOR BACTERIAL DETECTION）</news:title>
   <news:publication_date>2026-06-29T00:39:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706020</loc>
  <lastmod>2026-06-29T00:39:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的再ランク付けによるテキストスポッティングの改善（Visual Re-ranking with Natural Language Understanding for Text Spotting）</news:title>
   <news:publication_date>2026-06-29T00:39:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706018</loc>
  <lastmod>2026-06-29T00:38:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロジットペアリング手法は勾配ベース攻撃を欺ける（Logit Pairing Methods Can Fool Gradient-Based Attacks）</news:title>
   <news:publication_date>2026-06-29T00:38:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706016</loc>
  <lastmod>2026-06-29T00:37:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習におけるソフトウェア工学上の課題（Software Engineering Challenges of Deep Learning）</news:title>
   <news:publication_date>2026-06-29T00:37:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706014</loc>
  <lastmod>2026-06-29T00:37:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>明示的なユーザー・アイテム相互作用を組み込んだ深層強化学習による推薦（Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling）</news:title>
   <news:publication_date>2026-06-29T00:37:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706012</loc>
  <lastmod>2026-06-29T00:37:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カスケード型CNN-resBiLSTM-CTC：音声認識のためのエンドツーエンド音響モデル (CASCADED CNN-resBiLSTM-CTC: AN END-TO-END ACOUSTIC MODEL FOR SPEECH RECOGNITION)</news:title>
   <news:publication_date>2026-06-29T00:37:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706010</loc>
  <lastmod>2026-06-29T00:37:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepSymmetry によるタンデム反復と内部対称性の検出（DeepSymmetry: Using 3D convolutional networks for identification of tandem repeats and internal symmetries in protein structures）</news:title>
   <news:publication_date>2026-06-29T00:37:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706008</loc>
  <lastmod>2026-06-28T23:46:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトル変動に対処する拡張線形混合モデル（An Augmented Linear Mixing Model to Address Spectral Variability for Hyperspectral Unmixing）</news:title>
   <news:publication_date>2026-06-28T23:46:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706006</loc>
  <lastmod>2026-06-28T23:45:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型とデータ同化を組み合わせた物理過程の同定（Identification of physical processes via combined data-driven and data-assimilation methods）</news:title>
   <news:publication_date>2026-06-28T23:45:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706004</loc>
  <lastmod>2026-06-28T23:45:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GOT-10k：大規模高多様性トラッキングベンチマーク（GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the Wild）</news:title>
   <news:publication_date>2026-06-28T23:45:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706002</loc>
  <lastmod>2026-06-28T23:45:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴量バギングによるステガノグラファー識別（Feature Bagging for Steganographer Identification）</news:title>
   <news:publication_date>2026-06-28T23:45:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706000</loc>
  <lastmod>2026-06-28T23:45:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半クラウドソース型深層生成モデルによるクラスタリング（Semi-crowdsourced Clustering with Deep Generative Models）</news:title>
   <news:publication_date>2026-06-28T23:45:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705998</loc>
  <lastmod>2026-06-28T23:44:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Softmaxに替わる制御可能なスパースな代替手法（On Controllable Sparse Alternatives to Softmax）</news:title>
   <news:publication_date>2026-06-28T23:44:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705996</loc>
  <lastmod>2026-06-28T23:44:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>明示的フィードバックと暗黙的フィードバックの統合による推薦システム（Explicit Feedbacks Meet with Implicit Feedbacks: A Combined Approach for Recommendation System）</news:title>
   <news:publication_date>2026-06-28T23:44:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705994</loc>
  <lastmod>2026-06-28T22:53:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>古典と量子機械学習の融合による肺がんサブタイプ分類（An Amalgamation of Classical and Quantum Machine Learning For the Classification of Adenocarcinoma and Squamous Cell Carcinoma Patients）</news:title>
   <news:publication_date>2026-06-28T22:53:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705992</loc>
  <lastmod>2026-06-28T22:52:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピッチアクセント言語のための自己注意を用いたTacotron音声合成システムの検討 (INVESTIGATION OF ENHANCED TACOTRON TEXT-TO-SPEECH SYNTHESIS SYSTEMS WITH SELF-ATTENTION FOR PITCH ACCENT LANGUAGE)</news:title>
   <news:publication_date>2026-06-28T22:52:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705990</loc>
  <lastmod>2026-06-28T22:52:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化する自己表現モデルによる部分空間クラスタリング（Evolutionary Self-Expressive Models for Subspace Clustering）</news:title>
   <news:publication_date>2026-06-28T22:52:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705988</loc>
  <lastmod>2026-06-28T22:52:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ分布の変化を「大声で」検出する仕組み（Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift）</news:title>
   <news:publication_date>2026-06-28T22:52:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705986</loc>
  <lastmod>2026-06-28T22:52:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビットコイン上の実体（エンティティ）識別の実務的インパクト（Characterizing Entities in the Bitcoin Blockchain）</news:title>
   <news:publication_date>2026-06-28T22:52:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705984</loc>
  <lastmod>2026-06-28T22:51:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>社会車両スウォームの視点と実装課題（Social Vehicle Swarms: Agent-based Model for Social-aware Internet of Vehicles）</news:title>
   <news:publication_date>2026-06-28T22:51:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705982</loc>
  <lastmod>2026-06-28T22:51:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構に基づく車両追跡手法（Attention-Mechanism-based Tracking Method for Intelligent Internet of Vehicles）</news:title>
   <news:publication_date>2026-06-28T22:51:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705980</loc>
  <lastmod>2026-06-28T22:00:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>STFTスペクトル損失による音声波形生成モデルの学習（STFT SPECTRAL LOSS FOR TRAINING A NEURAL SPEECH WAVEFORM MODEL）</news:title>
   <news:publication_date>2026-06-28T22:00:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705978</loc>
  <lastmod>2026-06-28T22:00:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルソース・フィルタ波形モデルによる音声合成の高速化（NEURAL SOURCE-FILTER-BASED WAVEFORM MODEL FOR STATISTICAL PARAMETRIC SPEECH SYNTHESIS）</news:title>
   <news:publication_date>2026-06-28T22:00:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705976</loc>
  <lastmod>2026-06-28T21:59:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>裾適応fダイバージェンスを用いた変分推論（Variational Inference with Tail-adaptive f-Divergence）</news:title>
   <news:publication_date>2026-06-28T21:59:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705974</loc>
  <lastmod>2026-06-28T21:59:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>三次元自然対流における不確かさ定量化と代理モデル（Uncertainty Quantification in Three Dimensional Natural Convection using Polynomial Chaos Expansion and Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-28T21:59:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705972</loc>
  <lastmod>2026-06-28T21:59:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポスト再電離宇宙における明るいクエーサーの完全サーベイ（FILLING IN THE QUASAR REDSHIFT GAP AT Z ∼5.5 II: A COMPLETE SURVEY OF LUMINOUS QUASARS IN THE POST-REIONIZATION UNIVERSE）</news:title>
   <news:publication_date>2026-06-28T21:59:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705970</loc>
  <lastmod>2026-06-28T21:58:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重要なクラウドインフラを予測的に守る確率モデル（An approach to predictively securing critical cloud infrastructures through probabilistic modeling）</news:title>
   <news:publication_date>2026-06-28T21:58:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705968</loc>
  <lastmod>2026-06-28T21:58:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>聞き方を学ぶ：時間・周波数注意モデルによる音響イベント検出（LEARNING HOW TO LISTEN: A TEMPORAL-FREQUENTIAL ATTENTION MODEL FOR SOUND EVENT DETECTION）</news:title>
   <news:publication_date>2026-06-28T21:58:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705966</loc>
  <lastmod>2026-06-28T21:07:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>赤方偏移7.02で発見された朗明なBALクエーサーの発見（The Discovery of A Luminous Broad Absorption Line Quasar at A Redshift of 7.02）</news:title>
   <news:publication_date>2026-06-28T21:07:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705964</loc>
  <lastmod>2026-06-28T21:07:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Parameterized Quantum Circuitsの表現力（The Expressive Power of Parameterized Quantum Circuits）</news:title>
   <news:publication_date>2026-06-28T21:07:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705962</loc>
  <lastmod>2026-06-28T21:07:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AutoIntによる特徴相互作用の自動学習（AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks）</news:title>
   <news:publication_date>2026-06-28T21:07:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705960</loc>
  <lastmod>2026-06-28T21:06:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的事例に対する一般化の理論的理解（Rademacher Complexity for Adversarially Robust Generalization）</news:title>
   <news:publication_date>2026-06-28T21:06:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705958</loc>
  <lastmod>2026-06-28T21:06:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト適応型生成対抗ネットワークによる自然言語での画像操作（Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language）</news:title>
   <news:publication_date>2026-06-28T21:06:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705956</loc>
  <lastmod>2026-06-28T21:06:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>システムログ処理の高速化と半教師あり学習（Accelerating System Log Processing by Semi-supervised Learning）</news:title>
   <news:publication_date>2026-06-28T21:06:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705954</loc>
  <lastmod>2026-06-28T21:05:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>保護栽培環境向けスイートペッパー収穫ロボット（A Sweet Pepper Harvesting Robot for Protected Cropping Environments）</news:title>
   <news:publication_date>2026-06-28T21:05:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705952</loc>
  <lastmod>2026-06-28T20:14:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層構造データの確率的クラスタリングと複合輸送距離（Probabilistic Multilevel Clustering via Composite Transportation Distance）</news:title>
   <news:publication_date>2026-06-28T20:14:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705950</loc>
  <lastmod>2026-06-28T20:14:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>忘れずに学ぶ学習法（Learning to Learn Without Forgetting by Maximizing Transfer and Minimizing Interference）</news:title>
   <news:publication_date>2026-06-28T20:14:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705948</loc>
  <lastmod>2026-06-28T20:13:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフニューラルネットワークの平均場理論による分割性能の解明（Mean-field theory of graph neural networks in graph partitioning）</news:title>
   <news:publication_date>2026-06-28T20:13:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705946</loc>
  <lastmod>2026-06-28T20:12:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースロジスティック回帰による離散対向グラフモデルの学習（Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models）</news:title>
   <news:publication_date>2026-06-28T20:12:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705944</loc>
  <lastmod>2026-06-28T20:12:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MMDネットワークによる半教師付き翻訳（Semi-Supervised Translation with MMD Networks）</news:title>
   <news:publication_date>2026-06-28T20:12:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705942</loc>
  <lastmod>2026-06-28T20:12:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模グラフを効率的に学習する仕組み（Accurate, Efficient and Scalable Graph Embedding）</news:title>
   <news:publication_date>2026-06-28T20:12:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705940</loc>
  <lastmod>2026-06-28T20:11:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散テンソル分解のスムーズ解析（Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons）</news:title>
   <news:publication_date>2026-06-28T20:11:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705938</loc>
  <lastmod>2026-06-28T19:21:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非並列テキスト転換の教師なし評価指標と学習基準（Unsupervised Evaluation Metrics and Learning Criteria for Non-Parallel Textual Transfer）</news:title>
   <news:publication_date>2026-06-28T19:21:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705936</loc>
  <lastmod>2026-06-28T19:20:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相関の強いGPポスターの効率的サンプリングを可能にするRMHMCの実装（An Efficient Implementation of Riemannian Manifold Hamiltonian Monte Carlo for Gaussian Process Models）</news:title>
   <news:publication_date>2026-06-28T19:20:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705934</loc>
  <lastmod>2026-06-28T19:20:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>材料シミュレーションのための均一に高精度な原子間ポテンシャルの能動学習（Active Learning of Uniformly Accurate Inter-atomic Potentials for Materials Simulation）</news:title>
   <news:publication_date>2026-06-28T19:20:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705932</loc>
  <lastmod>2026-06-28T19:19:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変化面──多次元的変化点と反事実予測（Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction）</news:title>
   <news:publication_date>2026-06-28T19:19:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705930</loc>
  <lastmod>2026-06-28T19:19:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胎児心エコー動画における局所時空間解剖学的位置特定（SEQUENTIAL ANATOMY LOCALIZATION IN FETAL ECHOCARDIOGRAPHY VIDEO）</news:title>
   <news:publication_date>2026-06-28T19:19:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705928</loc>
  <lastmod>2026-06-28T19:19:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コスト意識的因果グラフ学習の実験デザイン（Experimental Design for Cost-Aware Learning of Causal Graphs）</news:title>
   <news:publication_date>2026-06-28T19:19:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705926</loc>
  <lastmod>2026-06-28T19:19:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汚れた訓練データから学ぶ反復トリム損失最小化（Learning with Bad Training Data via Iterative Trimmed Loss Minimization）</news:title>
   <news:publication_date>2026-06-28T19:19:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705924</loc>
  <lastmod>2026-06-28T18:28:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>上位ρ分位からk本の腕を選ぶ探索手法の考察（Exploring k out of Top ρ Fraction of Arms in Stochastic Bandits）</news:title>
   <news:publication_date>2026-06-28T18:28:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705922</loc>
  <lastmod>2026-06-28T18:27:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙の夜明けにおける21cm信号の解析的定式化（Analytic Formulation of 21 cm Signal from Cosmic Dawn: Lyα Fluctuations）</news:title>
   <news:publication_date>2026-06-28T18:27:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705920</loc>
  <lastmod>2026-06-28T18:27:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LPCNetによる低コスト音声合成（LPCNet: IMPROVING NEURAL SPEECH SYNTHESIS THROUGH LINEAR PREDICTION）</news:title>
   <news:publication_date>2026-06-28T18:27:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705918</loc>
  <lastmod>2026-06-28T18:26:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>資源制約下で「最大値」を狙うオンライン学習フレームワーク（MaxHedge: Maximising a Maximum Online）</news:title>
   <news:publication_date>2026-06-28T18:26:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705916</loc>
  <lastmod>2026-06-28T18:26:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模視覚データを機械学習向けに高速に扱う仕組み（VDMS: Efficient Big-Visual-Data Access for Machine Learning Workloads）</news:title>
   <news:publication_date>2026-06-28T18:26:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705914</loc>
  <lastmod>2026-06-28T18:25:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像ノイズ除去のための強化畳み込みニューラルネットワーク（Enhanced CNN for image denoising）</news:title>
   <news:publication_date>2026-06-28T18:25:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705912</loc>
  <lastmod>2026-06-28T18:25:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>雲を「ノイズ」と見なす衛星画像の頑健なセグメンテーション（Convolutional LSTMs for Cloud-Robust Segmentation of Remote Sensing Imagery）</news:title>
   <news:publication_date>2026-06-28T18:25:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705910</loc>
  <lastmod>2026-06-28T17:34:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>専門家助言の統合による差別保持の問題（On preserving non-discrimination when combining expert advice）</news:title>
   <news:publication_date>2026-06-28T17:34:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705908</loc>
  <lastmod>2026-06-28T17:34:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパースペクトル動画における物体追跡の新手法（Object Tracking in Hyperspectral Videos with Convolutional Features and Kernelized Correlation Filter）</news:title>
   <news:publication_date>2026-06-28T17:34:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705906</loc>
  <lastmod>2026-06-28T17:34:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーグラフに基づく半教師あり学習アルゴリズムの音声認識への適用（Hypergraph Based Semi-Supervised Learning Algorithms Applied to Speech Recognition Problem）</news:title>
   <news:publication_date>2026-06-28T17:34:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705904</loc>
  <lastmod>2026-06-28T17:33:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>識別力を重視したチャネル削減（Discrimination-aware Channel Pruning for Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-28T17:33:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705902</loc>
  <lastmod>2026-06-28T17:33:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TV事前情報を用いた画像超解像の実用的意味（Image Super-Resolution Using TV Priori Guided Convolutional Network）</news:title>
   <news:publication_date>2026-06-28T17:33:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705900</loc>
  <lastmod>2026-06-28T17:33:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボットが「ノー」を学ぶ――否定語獲得における禁止と拒否のメカニズム（Robots Learning to Say ‘No’: Prohibition and Rejective Mechanisms in Acquisition of Linguistic Negation）</news:title>
   <news:publication_date>2026-06-28T17:33:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705898</loc>
  <lastmod>2026-06-28T17:32:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>四次元におけるボソン—フェルミオン双対性（Boson-fermion duality in four dimensions）</news:title>
   <news:publication_date>2026-06-28T17:32:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705896</loc>
  <lastmod>2026-06-28T16:41:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>陽子スピンの深い混合（Proton Spin in Deep Inelastic Scattering）</news:title>
   <news:publication_date>2026-06-28T16:41:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705894</loc>
  <lastmod>2026-06-28T16:41:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークの分散学習ガイド（A Hitchhiker’s Guide On Distributed Training of Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-28T16:41:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705892</loc>
  <lastmod>2026-06-28T16:41:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理世界で機能する音声の敵対的事例の生成（Robust Audio Adversarial Example for a Physical Attack）</news:title>
   <news:publication_date>2026-06-28T16:41:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705890</loc>
  <lastmod>2026-06-28T16:41:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰的ヤコビアン境界アルゴリズム RecurJac（RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications）</news:title>
   <news:publication_date>2026-06-28T16:41:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705888</loc>
  <lastmod>2026-06-28T16:40:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Affinity Network による複数物体追跡の再設計（Deep Affinity Network for Multiple Object Tracking）</news:title>
   <news:publication_date>2026-06-28T16:40:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705886</loc>
  <lastmod>2026-06-28T16:40:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パリティ奇数のニュートリノトルク検出（Parity-odd neutrino torque detection）</news:title>
   <news:publication_date>2026-06-28T16:40:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705884</loc>
  <lastmod>2026-06-28T16:40:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的系における安定で予測可能な構造の学習（Learning stable and predictive structures in kinetic systems: Benefits of a causal approach）</news:title>
   <news:publication_date>2026-06-28T16:40:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705882</loc>
  <lastmod>2026-06-28T15:49:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解析モデルと機械学習の融合による性能予測（Learning with Analytical Models）</news:title>
   <news:publication_date>2026-06-28T15:49:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705880</loc>
  <lastmod>2026-06-28T15:49:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シナプスから空間記憶地図へ（Through synapses to spatial memory maps: a topological model）</news:title>
   <news:publication_date>2026-06-28T15:49:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705878</loc>
  <lastmod>2026-06-28T15:48:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感度駆動型正則化によるスパースニューラルネット学習（Learning Sparse Neural Networks via Sensitivity-Driven Regularization）</news:title>
   <news:publication_date>2026-06-28T15:48:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705876</loc>
  <lastmod>2026-06-28T15:48:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模ネットワークの中心性を学習で高速化する研究（Computing Vertex Centrality Measures in Massive Real Networks with a Neural Learning Model）</news:title>
   <news:publication_date>2026-06-28T15:48:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705874</loc>
  <lastmod>2026-06-28T15:48:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習とリザバーコンピューティングによる分散型動的スペクトラムアクセス（Distributive Dynamic Spectrum Access through Deep Reinforcement Learning: A Reservoir Computing Based Approach）</news:title>
   <news:publication_date>2026-06-28T15:48:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705872</loc>
  <lastmod>2026-06-28T15:47:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観察されていないものを見る：並列化されたモンテカルロ木探索の単純なアプローチ（WATCH THE UNOBSERVED: A SIMPLE APPROACH TO PARALLELIZING MONTE CARLO TREE SEARCH）</news:title>
   <news:publication_date>2026-06-28T15:47:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705870</loc>
  <lastmod>2026-06-28T15:47:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク中心性指標における機械学習による近似手法（Machine Learning in Network Centrality Measures: Tutorial and Outlook）</news:title>
   <news:publication_date>2026-06-28T15:47:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705868</loc>
  <lastmod>2026-06-28T14:56:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルコフ連鎖の学習（On Learning Markov Chains）</news:title>
   <news:publication_date>2026-06-28T14:56:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705866</loc>
  <lastmod>2026-06-28T14:56:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習表現の理解に向けて：異なるニューラルネットワークはどの程度同じ表現を学ぶか (Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation)</news:title>
   <news:publication_date>2026-06-28T14:56:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705864</loc>
  <lastmod>2026-06-28T14:56:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DQN-TAMERによる人間-in-the-loop強化学習（DQN-TAMER: Human-in-the-Loop Reinforcement Learning with Intractable Feedback）</news:title>
   <news:publication_date>2026-06-28T14:56:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705862</loc>
  <lastmod>2026-06-28T14:55:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>残差ニューラルネットワークの深層極限（Deep Limits of Residual Neural Networks）</news:title>
   <news:publication_date>2026-06-28T14:55:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705860</loc>
  <lastmod>2026-06-28T14:54:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程事前分布付き変分オートエンコーダ（Gaussian Process Prior Variational Autoencoders）</news:title>
   <news:publication_date>2026-06-28T14:54:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705858</loc>
  <lastmod>2026-06-28T14:54:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形動力学のサンプル複雑度（Sample Complexity for Nonlinear Dynamics）</news:title>
   <news:publication_date>2026-06-28T14:54:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705856</loc>
  <lastmod>2026-06-28T14:54:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANに対する凸双対性フレームワークの示唆（A Convex Duality Framework for GANs）</news:title>
   <news:publication_date>2026-06-28T14:54:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705854</loc>
  <lastmod>2026-06-28T14:03:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>専用モジュールネットワークの類似性基準による訓練によるリアルタイム行動認識 (Real-time Action Recognition with Dissimilarity-based Training of Specialized Module Networks)</news:title>
   <news:publication_date>2026-06-28T14:03:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705852</loc>
  <lastmod>2026-06-28T14:02:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワークにおけるクリティカルパスの蒸留（Distilling Critical Paths in Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-28T14:02:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705850</loc>
  <lastmod>2026-06-28T14:02:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共分散保存型敵対的拡張ネットワーク（Low-shot Learning via Covariance-Preserving Adversarial Augmentation Networks）</news:title>
   <news:publication_date>2026-06-28T14:02:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705848</loc>
  <lastmod>2026-06-28T14:01:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CoSTARによるブロック積みデータセットとワークスペース制約（The CoSTAR Block Stacking Dataset: Learning with Workspace Constraints）</news:title>
   <news:publication_date>2026-06-28T14:01:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705846</loc>
  <lastmod>2026-06-28T14:01:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FGSMの正則化効果とその一般化（Regularization Effect of Fast Gradient Sign Method and its Generalization）</news:title>
   <news:publication_date>2026-06-28T14:01:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705844</loc>
  <lastmod>2026-06-28T14:01:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>堅牢な深層ニューラルネットワークの探索（Towards Robust Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-28T14:01:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705842</loc>
  <lastmod>2026-06-28T14:01:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数グループNB‑IoTネットワークの協調深層強化学習による最適化（Cooperative Deep Reinforcement Learning for Multiple-Group NB-IoT Networks Optimization）</news:title>
   <news:publication_date>2026-06-28T14:01:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705840</loc>
  <lastmod>2026-06-28T13:10:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報欠損に基づく表現学習の新潮流：Variational Deficiency Bottleneck（The Variational Deficiency Bottleneck）</news:title>
   <news:publication_date>2026-06-28T13:10:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705838</loc>
  <lastmod>2026-06-28T13:01:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インテリジェント・ナノフォトニクス：ナノスケールで光学と人工知能を融合する研究（Intelligent Nanophotonics: Merging Photonics and Artificial Intelligence at the Nanoscale）</news:title>
   <news:publication_date>2026-06-28T13:01:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705836</loc>
  <lastmod>2026-06-28T13:00:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチエージェント共通知識強化学習（Multi-Agent Common Knowledge）</news:title>
   <news:publication_date>2026-06-28T13:00:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705834</loc>
  <lastmod>2026-06-28T13:00:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワイヤレスバックスキャッタで繰り返し動作を認識・計測する（From Communication to Sensing: Recognizing and Counting Repetitive Motions with Wireless Backscattering）</news:title>
   <news:publication_date>2026-06-28T13:00:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705832</loc>
  <lastmod>2026-06-28T13:00:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stein Variational Gradient Descentのモーメント一致性（Stein Variational Gradient Descent as Moment Matching）</news:title>
   <news:publication_date>2026-06-28T13:00:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705830</loc>
  <lastmod>2026-06-28T13:00:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実な入力を扱う回帰木（Uncertain Trees: Dealing with Uncertain Inputs in Regression Trees）</news:title>
   <news:publication_date>2026-06-28T13:00:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705828</loc>
  <lastmod>2026-06-28T12:59:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>主成分分析と深層ニューラルネットワークによる船体最適化（Hull Form Optimization with Principal Component Analysis and Deep Neural Network）</news:title>
   <news:publication_date>2026-06-28T12:59:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705826</loc>
  <lastmod>2026-06-28T12:08:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロブログを用いた疑わしいニュース検出（Suspicious News Detection Using Micro Blog Text）</news:title>
   <news:publication_date>2026-06-28T12:08:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705824</loc>
  <lastmod>2026-06-28T11:59:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートシティにおけるSDN・AI・ビッグデータの統合的活用（Towards Smart City Innovation Under the Perspective of Software-Defined Networking, Artificial Intelligence and Big Data）</news:title>
   <news:publication_date>2026-06-28T11:59:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705822</loc>
  <lastmod>2026-06-28T11:59:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒエラルキー型ソフトマックスのXMLCへの無後悔一般化（A no-regret generalization of hierarchical softmax to extreme multi-label classification）</news:title>
   <news:publication_date>2026-06-28T11:59:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705820</loc>
  <lastmod>2026-06-28T11:58:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハーディのパラドックスを用いた実用的なノーシグナリング証明ランダムネス増幅と実験実装 (Practical No-Signalling proof Randomness Amplification using Hardy paradoxes and its experimental implementation)</news:title>
   <news:publication_date>2026-06-28T11:58:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705818</loc>
  <lastmod>2026-06-28T11:58:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みネットワークとアダマールネットワークの等価性（On the Equivalence of Convolutional and Hadamard Networks using DFT）</news:title>
   <news:publication_date>2026-06-28T11:58:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705816</loc>
  <lastmod>2026-06-28T11:58:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラウザで協働設計するニューラルネットワーク編集ツール（Fabrik: An online collaborative neural network editor）</news:title>
   <news:publication_date>2026-06-28T11:58:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705814</loc>
  <lastmod>2026-06-28T11:58:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>活性化関数の自動選択手法によるハイブリッド深層ニューラルネットワーク設計（A Methodology for Automatic Selection of Activation Functions to Design Hybrid Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-28T11:58:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705812</loc>
  <lastmod>2026-06-28T11:06:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>区間タイプの特徴化に基づく時系列クラスタリング（Time series clustering based on the characterisation of segment typologies）</news:title>
   <news:publication_date>2026-06-28T11:06:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705810</loc>
  <lastmod>2026-06-28T10:58:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆方向（後方角度）でのω光生成過程における核子Reggeonとパートン寄与の役割（Features of ω photoproduction off proton target at backward angles : Role of nucleon Reggeon in u-channel with parton contributions）</news:title>
   <news:publication_date>2026-06-28T10:58:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705808</loc>
  <lastmod>2026-06-28T10:57:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実験データで観察データの隠れ交絡を是正する方法（Removing Hidden Confounding by Experimental Grounding）</news:title>
   <news:publication_date>2026-06-28T10:57:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705806</loc>
  <lastmod>2026-06-28T10:57:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RGBとDepthを横断する人物再識別のためのクロスモーダル蒸留（Cross-Modal Distillation for Person Re-Identification）</news:title>
   <news:publication_date>2026-06-28T10:57:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705804</loc>
  <lastmod>2026-06-28T10:57:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による雑音除去の実践と意義（Deep learning for denoising）</news:title>
   <news:publication_date>2026-06-28T10:57:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705802</loc>
  <lastmod>2026-06-28T10:56:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル比較のための判別的特徴抽出（Informative Features for Model Comparison）</news:title>
   <news:publication_date>2026-06-28T10:56:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705800</loc>
  <lastmod>2026-06-28T10:56:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集団知能のエージェントベースモデル入門（Agent-based models of collective intelligence）</news:title>
   <news:publication_date>2026-06-28T10:56:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705798</loc>
  <lastmod>2026-06-28T10:05:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡データを扱うマルチラベル分類の改善（Handling Imbalanced Dataset in Multi-label Text Categorization using Bagging and Adaptive Boosting）</news:title>
   <news:publication_date>2026-06-28T10:05:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705796</loc>
  <lastmod>2026-06-28T10:05:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTのための学習と管理：適応性とスケーラビリティへの挑戦（Learning and Management for Internet-of-Things: Accounting for Adaptivity and Scalability）</news:title>
   <news:publication_date>2026-06-28T10:05:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705794</loc>
  <lastmod>2026-06-28T10:05:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトゲート型Warping-GANによる姿勢誘導人物画像生成（Soft-Gated Warping-GAN for Pose-Guided Person Image Synthesis）</news:title>
   <news:publication_date>2026-06-28T10:05:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705792</loc>
  <lastmod>2026-06-28T10:04:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非局所フロッキング動力学：粒子シミュレーションからPDEの分数次数を学習する（Nonlocal flocking dynamics: Learning the fractional order of PDEs from particle simulations）</news:title>
   <news:publication_date>2026-06-28T10:04:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705790</loc>
  <lastmod>2026-06-28T10:04:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼できる予測確率の調整法の実務的進化（Attended Temperature Scaling: A Practical Approach for Calibrating Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-28T10:04:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705788</loc>
  <lastmod>2026-06-28T10:04:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>忘却に対抗する自己教師ありGAN（Self-Supervised GAN to Counter Forgetting）</news:title>
   <news:publication_date>2026-06-28T10:04:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705786</loc>
  <lastmod>2026-06-28T10:04:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>余クラス受容野を持つ畳み込みニューラルネットワーク（Convolutional neural networks with extra-classical receptive fields）</news:title>
   <news:publication_date>2026-06-28T10:04:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705784</loc>
  <lastmod>2026-06-28T09:13:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈性に基づく敵対サンプル検出（Attacks Meet Interpretability: Attribute-steered Detection of Adversarial Samples）</news:title>
   <news:publication_date>2026-06-28T09:13:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705782</loc>
  <lastmod>2026-06-28T09:12:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネルとレンジ空間に基づく勾配不要学習（Gradient-Free Learning Based on the Kernel and the Range Space）</news:title>
   <news:publication_date>2026-06-28T09:12:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705780</loc>
  <lastmod>2026-06-28T09:12:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習による抽象オプションの階層化（Learning Abstract Options）</news:title>
   <news:publication_date>2026-06-28T09:12:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705778</loc>
  <lastmod>2026-06-28T09:12:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長距離特徴伝播を効率化する二重注意機構（A2-Nets: Double Attention Networks）</news:title>
   <news:publication_date>2026-06-28T09:12:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705776</loc>
  <lastmod>2026-06-28T09:11:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短セグメント心音分類のための深層畳み込みニューラルネットワークアンサンブル（Short-segment heart sound classification using an ensemble of deep convolutional neural networks）</news:title>
   <news:publication_date>2026-06-28T09:11:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705774</loc>
  <lastmod>2026-06-28T09:11:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>滑らかな分布に対するkNN情報推定量の解析（Analysis of KNN Information Estimators for Smooth Distributions）</news:title>
   <news:publication_date>2026-06-28T09:11:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705772</loc>
  <lastmod>2026-06-28T09:11:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳腫瘍セグメンテーションの体積畳み込みニューラルネットワーク（A Volumetric Convolutional Neural Network for Brain Tumor Segmentation）</news:title>
   <news:publication_date>2026-06-28T09:11:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705770</loc>
  <lastmod>2026-06-28T08:20:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルセンサデータの匿名化（Mobile Sensor Data Anonymization）</news:title>
   <news:publication_date>2026-06-28T08:20:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705768</loc>
  <lastmod>2026-06-28T08:11:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>明示的・暗黙的コミュニケーションによる効率的で信頼できる社会的ナビゲーション（Efficient and Trustworthy Social Navigation Via Explicit and Implicit Robot-Human Communication）</news:title>
   <news:publication_date>2026-06-28T08:11:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705766</loc>
  <lastmod>2026-06-28T08:11:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床精神医学で解釈可能な推論を実現するMCAルールマイニング (MCA-based Rule Mining Enables Interpretable Inference in Clinical Psychiatry)</news:title>
   <news:publication_date>2026-06-28T08:11:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705764</loc>
  <lastmod>2026-06-28T08:10:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>気象とサウンドスケープの形状を監視する新しい統計手法（Monitoring the shape of weather, soundscapes, and dynamical systems: a new statistic for dimension-driven data analysis on large data sets）</news:title>
   <news:publication_date>2026-06-28T08:10:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705762</loc>
  <lastmod>2026-06-28T08:10:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般確率空間における多変量情報量の推定器（Estimators for Multivariate Information Measures in General Probability Spaces）</news:title>
   <news:publication_date>2026-06-28T08:10:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705760</loc>
  <lastmod>2026-06-28T08:10:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間のデモと介入を効率的に組み合わせた安全なリアルタイム学習（Efficiently Combining Human Demonstrations and Interventions for Safe Training of Autonomous Systems in Real-Time）</news:title>
   <news:publication_date>2026-06-28T08:10:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705758</loc>
  <lastmod>2026-06-28T08:10:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>監視映像の品質を自動判定する深層畳み込みネットワーク（DEEP CONVOLUTIONAL NEURAL NETWORK APPLIED TO QUALITY ASSESSMENT FOR VIDEO TRACKING）</news:title>
   <news:publication_date>2026-06-28T08:10:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705756</loc>
  <lastmod>2026-06-28T07:18:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトログラム・チャンネルU-Net：音源分離を直観的に解く（SPECTROGRAM-CHANNELS U-NET: A SOURCE SEPARATION MODEL）</news:title>
   <news:publication_date>2026-06-28T07:18:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705754</loc>
  <lastmod>2026-06-28T07:11:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>凸であっても不整合な代替損失関数の学習保証の定量化（Quantifying Learning Guarantees for Convex but Inconsistent Surrogates）</news:title>
   <news:publication_date>2026-06-28T07:11:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705752</loc>
  <lastmod>2026-06-28T07:11:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地震カタログに基づく機械学習による実験室断層状態の識別と完全度閾値の影響（Earthquake catalog-based machine learning identification of laboratory fault states and the effects of magnitude of completeness）</news:title>
   <news:publication_date>2026-06-28T07:11:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705750</loc>
  <lastmod>2026-06-28T07:10:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Attentionベース階層デコーダによるGUIからの自動コード生成（Automatic Graphics Program Generation using Attention-Based Hierarchical Decoder）</news:title>
   <news:publication_date>2026-06-28T07:10:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705748</loc>
  <lastmod>2026-06-28T07:10:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多重袋（bags-of-bags）で学ぶネットワーク設計の革新 — LEARNING AND INTERPRETING MULTI-MULTI-INSTANCE LEARNING NETWORKS (LEARNING AND INTERPRETING MULTI-MULTI-INSTANCE LEARNING NETWORKS)</news:title>
   <news:publication_date>2026-06-28T07:10:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705746</loc>
  <lastmod>2026-06-28T07:09:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Whetstoneによる二値通信ニューラルネットワーク訓練法（Whetstone: A Method for Training Deep Artificial Neural Networks for Binary Communication）</news:title>
   <news:publication_date>2026-06-28T07:09:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705744</loc>
  <lastmod>2026-06-28T07:09:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動微分の現在地と進むべき方向（Automatic differentiation in ML: Where we are and where we should be going）</news:title>
   <news:publication_date>2026-06-28T07:09:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705742</loc>
  <lastmod>2026-06-28T06:18:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相空間積分に対するニューラルネットワークアプローチ (Neural Network-Based Approach to Phase Space Integration)</news:title>
   <news:publication_date>2026-06-28T06:18:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705740</loc>
  <lastmod>2026-06-28T06:18:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NMBS-IIフィールドにおけるIRAC深層モザイク化の意義（IRAC mapping of the NMBS-II fields）</news:title>
   <news:publication_date>2026-06-28T06:18:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705738</loc>
  <lastmod>2026-06-28T06:17:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模経験的リスク最小化のための効率的分散ヘッセ非依存アルゴリズム（Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy）</news:title>
   <news:publication_date>2026-06-28T06:17:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705736</loc>
  <lastmod>2026-06-28T06:17:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定性保証付き強化学習：制御理論的視点での検証（STABILITY-CERTIFIED REINFORCEMENT LEARNING: A CONTROL-THEORETIC PERSPECTIVE）</news:title>
   <news:publication_date>2026-06-28T06:17:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705734</loc>
  <lastmod>2026-06-28T06:17:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルメディアから救援ニーズを自動抽出・順位付けする手法（Automatic Identification and Ranking of Emergency Aids in Social Media Macro Community）</news:title>
   <news:publication_date>2026-06-28T06:17:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705732</loc>
  <lastmod>2026-06-28T06:17:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散学習における情報ボトルネック法（Information Bottleneck Methods for Distributed Learning）</news:title>
   <news:publication_date>2026-06-28T06:17:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705730</loc>
  <lastmod>2026-06-28T06:16:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的パラメータの機械学習による推定（Machine learning determination of dynamical parameters: The Ising model case）</news:title>
   <news:publication_date>2026-06-28T06:16:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705728</loc>
  <lastmod>2026-06-28T05:25:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>次世代電波望遠鏡による系外惑星のトランジット観測（Exoplanet Transits with Next-Generation Radio Telescopes）</news:title>
   <news:publication_date>2026-06-28T05:25:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705726</loc>
  <lastmod>2026-06-28T05:25:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話し言葉の協調構造解析（Parsing Coordination for Spoken Language Understanding）</news:title>
   <news:publication_date>2026-06-28T05:25:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705724</loc>
  <lastmod>2026-06-28T05:25:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>比較ベースのサロゲートモデルと能動的共分散行列適応を用いた文脈付き方策探索の実証評価 (Empirical Evaluation of Contextual Policy Search with a Comparison-based Surrogate Model and Active Covariance Matrix Adaptation)</news:title>
   <news:publication_date>2026-06-28T05:25:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705722</loc>
  <lastmod>2026-06-28T05:24:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANを使ったスケーラブルなアンバランス最適輸送の実装戦略（SCALABLE UNBALANCED OPTIMAL TRANSPORT USING GENERATIVE ADVERSARIAL NETWORKS）</news:title>
   <news:publication_date>2026-06-28T05:24:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705720</loc>
  <lastmod>2026-06-28T05:24:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層反応性方策の転移によるMDP計画（Transfer of Deep Reactive Policies for MDP Planning）</news:title>
   <news:publication_date>2026-06-28T05:24:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705718</loc>
  <lastmod>2026-06-28T05:24:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生涯オンライン学習のための知識蓄積（Accumulating Knowledge for Lifelong Online Learning）</news:title>
   <news:publication_date>2026-06-28T05:24:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705716</loc>
  <lastmod>2026-06-28T05:23:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前処理不要の計算的組織染色と脱染の実現（Computational Histological Staining and Destaining of Prostate Core Biopsy RGB Images with Generative Adversarial Neural Networks）</news:title>
   <news:publication_date>2026-06-28T05:23:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705714</loc>
  <lastmod>2026-06-28T04:33:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TanDEM-XとCartosat-1の標高データ融合による都市域DEM精度向上（Fusion of TanDEM-X and Cartosat-1 Elevation Data Supported by Neural Network-Predicted Weight Maps）</news:title>
   <news:publication_date>2026-06-28T04:33:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705712</loc>
  <lastmod>2026-06-28T04:32:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VAEの事前分布を再サンプリングする手法（Resampled Priors for Variational Autoencoders）</news:title>
   <news:publication_date>2026-06-28T04:32:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705710</loc>
  <lastmod>2026-06-28T04:32:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子カルテの退院サマリーの抽出的要約（Extractive Summarization of Electronic Health Record Discharge Notes）</news:title>
   <news:publication_date>2026-06-28T04:32:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705708</loc>
  <lastmod>2026-06-28T04:32:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>樹状突起を用いた皮質マイクロ回路は逆伝播を近似する (Dendritic cortical microcircuits approximate the backpropagation algorithm)</news:title>
   <news:publication_date>2026-06-28T04:32:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705706</loc>
  <lastmod>2026-06-28T04:32:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚情報からの連続動作学習を効率化する深層内発的動機づけアクター・クリティック（Deep intrinsically motivated continuous actor-critic for efficient robotic visuomotor skill learning）</news:title>
   <news:publication_date>2026-06-28T04:32:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705704</loc>
  <lastmod>2026-06-28T04:32:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散型IoTシステムのための新興エッジコンピューティング技術（Emerging Edge Computing Technologies for Distributed Internet of Things (IoT) Systems）</news:title>
   <news:publication_date>2026-06-28T04:32:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705702</loc>
  <lastmod>2026-06-28T04:31:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル向け随時ステレオ画像深度推定（Anytime Stereo Image Depth Estimation on Mobile Devices）</news:title>
   <news:publication_date>2026-06-28T04:31:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705700</loc>
  <lastmod>2026-06-28T03:40:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノックオフ手法の安定化（Stabilizing Knockoffs: Multiple Simultaneous Knockoffs and Entropy Maximization）</news:title>
   <news:publication_date>2026-06-28T03:40:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705698</loc>
  <lastmod>2026-06-28T03:40:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>システムピークへの寄与に基づくデータ駆動型顧客セグメンテーション（A Data-Driven Customer Segmentation Strategy Based on Contribution to System Peak Demand）</news:title>
   <news:publication_date>2026-06-28T03:40:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705696</loc>
  <lastmod>2026-06-28T03:40:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPUで加速する室内インパルス応答シミュレーション用Pythonライブラリ（gpuRIR: A Python Library for Room Impulse Response Simulation with GPU Acceleration）</news:title>
   <news:publication_date>2026-06-28T03:40:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705694</loc>
  <lastmod>2026-06-28T03:39:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成モデルを用いた外れ値検出の理論と実装（Outlier Detection using Generative Models with Theoretical Performance Guarantees）</news:title>
   <news:publication_date>2026-06-28T03:39:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705692</loc>
  <lastmod>2026-06-28T03:39:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークによる分子の平衡構造生成（Generating equilibrium molecules with deep neural networks）</news:title>
   <news:publication_date>2026-06-28T03:39:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705690</loc>
  <lastmod>2026-06-28T03:39:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>過剰パラメータ化がEMにもたらす利点（Benefits of over-parameterization with EM）</news:title>
   <news:publication_date>2026-06-28T03:39:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705688</loc>
  <lastmod>2026-06-28T03:38:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピラミダルFSMNとラティスフリーMMIによる音声認識精度向上（A NOVEL PYRAMIDAL-FSMN ARCHITECTURE WITH LATTICE-FREE MMI FOR SPEECH RECOGNITION）</news:title>
   <news:publication_date>2026-06-28T03:38:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705686</loc>
  <lastmod>2026-06-28T02:47:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>見えない環境での音声強調を拡張するノイズ埋め込みと大規模環境学習（Scaling Speech Enhancement in Unseen Environments with Noise Embeddings）</news:title>
   <news:publication_date>2026-06-28T02:47:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705684</loc>
  <lastmod>2026-06-28T02:47:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バルカン地域のエネルギー消費予測における多層パーセプトロンと重回帰の比較（Comparing Multilayer Perceptron and Multiple Regression Models for Predicting Energy Use in the Balkans）</news:title>
   <news:publication_date>2026-06-28T02:47:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705682</loc>
  <lastmod>2026-06-28T02:47:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル端末で動くリアルタイム文脈学習とIoT制御（Real-time Context-aware Learning System for IoT Applications）</news:title>
   <news:publication_date>2026-06-28T02:47:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705680</loc>
  <lastmod>2026-06-28T02:46:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模銀河画像データベースのハイブリッド注釈手法（A hybrid approach to machine learning annotation of large galaxy image databases）</news:title>
   <news:publication_date>2026-06-28T02:46:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705678</loc>
  <lastmod>2026-06-28T02:46:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン学習における単一事例の複数回重み更新（Online learning using multiple times weight updating）</news:title>
   <news:publication_date>2026-06-28T02:46:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705676</loc>
  <lastmod>2026-06-28T02:46:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>聖書文脈でのドメイン適応：小規模データでの質問応答性能を高める手法（Finding Answers from the Word of God: Domain Adaptation for Neural Networks in Biblical Question Answering）</news:title>
   <news:publication_date>2026-06-28T02:46:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705674</loc>
  <lastmod>2026-06-28T01:55:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像における人物再識別を加速する空間・時間注意ネットワーク（Video-based Person Re-identification Using Spatial-Temporal Attention Networks）</news:title>
   <news:publication_date>2026-06-28T01:55:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705672</loc>
  <lastmod>2026-06-28T01:55:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スズの孤立電子対が招くキャリア捕獲の問題（Lone-pair effect on carrier capture in Cu2ZnSnS4 solar cells）</news:title>
   <news:publication_date>2026-06-28T01:55:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705670</loc>
  <lastmod>2026-06-28T01:54:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リーダーボードを超えて：InsightとDeploymentチャレンジの役割（Beyond the Leaderboard: Insight and Deployment Challenges to Address Research Problems）</news:title>
   <news:publication_date>2026-06-28T01:54:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705668</loc>
  <lastmod>2026-06-28T01:54:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミリ波V2XにおけるDeepRLベースの分散車両位置制御によるカバレッジ拡張（Deep-Reinforcement-Learning-Based Distributed Vehicle Position Controls for Coverage Expansion in mmWave V2X）</news:title>
   <news:publication_date>2026-06-28T01:54:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705666</loc>
  <lastmod>2026-06-28T01:54:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>直列結合同一DNNによる雑音型依存性の低減（CONCATENATED IDENTICAL DNN (CI-DNN) TO REDUCE NOISE-TYPE DEPENDENCE IN DNN-BASED SPEECH ENHANCEMENT）</news:title>
   <news:publication_date>2026-06-28T01:54:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705664</loc>
  <lastmod>2026-06-28T01:54:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CAPSULE-FORENSICSによる偽造画像・動画検出（CAPSULE-FORENSICS: USING CAPSULE NETWORKS TO DETECT FORGED IMAGES AND VIDEOS）</news:title>
   <news:publication_date>2026-06-28T01:54:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705662</loc>
  <lastmod>2026-06-28T01:54:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合モデルの大域収束をめざすCM-EMアルゴリズム（From the EM Algorithm to the CM-EM Algorithm for Global Convergence of Mixture Models）</news:title>
   <news:publication_date>2026-06-28T01:54:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705660</loc>
  <lastmod>2026-06-28T01:03:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HPC向けオンライン障害分類の実践（Online Fault Classification in HPC Systems through Machine Learning）</news:title>
   <news:publication_date>2026-06-28T01:03:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705658</loc>
  <lastmod>2026-06-28T01:03:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ポアソンガンマ動的システム（Deep Poisson gamma dynamical systems）</news:title>
   <news:publication_date>2026-06-28T01:03:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705656</loc>
  <lastmod>2026-06-28T01:03:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>4D OCTの最大強度投影に対する深層学習ベースの2.5Dフロー場推定（Deep learning based 2.5D flow field estimation for maximum intensity projections of 4D optical coherence tomography）</news:title>
   <news:publication_date>2026-06-28T01:03:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705654</loc>
  <lastmod>2026-06-28T01:02:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文章簡約のためのトランスフォーマとパラフレーズ規則の統合 (Integrating Transformer and Paraphrase Rules for Sentence Simplification)</news:title>
   <news:publication_date>2026-06-28T01:02:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705652</loc>
  <lastmod>2026-06-28T01:02:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CrystalGANで結晶構造を発見する（CrystalGAN: Learning to Discover Crystallographic Structures with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-28T01:02:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705650</loc>
  <lastmod>2026-06-28T01:02:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CubeSatにおける光通信の可能性（Optical Communication on CubeSats – Enabling the Next Era in Space Science –）</news:title>
   <news:publication_date>2026-06-28T01:02:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705648</loc>
  <lastmod>2026-06-28T01:01:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムフォレストの可逆（と非可逆）圧縮（Lossless (and Lossy) Compression of Random Forests）</news:title>
   <news:publication_date>2026-06-28T01:01:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705646</loc>
  <lastmod>2026-06-28T00:11:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特定相手を狙うマルチエージェント通信の設計（TarMAC: Targeted Multi-Agent Communication）</news:title>
   <news:publication_date>2026-06-28T00:11:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705644</loc>
  <lastmod>2026-06-28T00:11:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細粒度ビデオ分類における冗長性削減注意機構（Fine-grained Video Categorization with Redundancy Reduction Attention）</news:title>
   <news:publication_date>2026-06-28T00:11:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705642</loc>
  <lastmod>2026-06-28T00:10:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケールドデジタル学習環境におけるシーケンシャルなランダム化（Beyond A/B Testing: Sequential Randomization for Developing Interventions in Scaled Digital Learning Environments）</news:title>
   <news:publication_date>2026-06-28T00:10:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705640</loc>
  <lastmod>2026-06-28T00:10:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>住宅向けバッテリー最適運用における太陽光・負荷予測の活用（Using solar and load predictions in battery scheduling at the residential level）</news:title>
   <news:publication_date>2026-06-28T00:10:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705638</loc>
  <lastmod>2026-06-28T00:10:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>身体的問答のためのニューラル・モジュラー制御（Neural Modular Control for Embodied Question Answering）</news:title>
   <news:publication_date>2026-06-28T00:10:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705636</loc>
  <lastmod>2026-06-28T00:10:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>InversionNetによるフルウェーブフォーム反演の高速化と高精度化（InversionNet: A Real-Time and Accurate Full Waveform Inversion with CNNs and continuous CRFs）</news:title>
   <news:publication_date>2026-06-28T00:10:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705634</loc>
  <lastmod>2026-06-28T00:09:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース関係遷移モデルの学習（Learning Sparse Relational Transition Models）</news:title>
   <news:publication_date>2026-06-28T00:09:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705632</loc>
  <lastmod>2026-06-27T23:18:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散型マルチプレイヤーバンディットにおける通信不要の最適化（Game of Thrones: Fully Distributed Learning for Multi-Player Bandits）</news:title>
   <news:publication_date>2026-06-27T23:18:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705630</loc>
  <lastmod>2026-06-27T23:18:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔認識のデータ特化適応閾値（Data-specific Adaptive Threshold for Face Recognition and Authentication）</news:title>
   <news:publication_date>2026-06-27T23:18:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705628</loc>
  <lastmod>2026-06-27T23:18:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近傍表現を効率的に学習する Differentiable Boundary Sets（Efficient learning of neighbor representations for boundary trees and forests）</news:title>
   <news:publication_date>2026-06-27T23:18:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705626</loc>
  <lastmod>2026-06-27T23:17:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Size-Noise Tradeoffs in Generative Networks（Size-Noise Tradeoffs in Generative Networks）</news:title>
   <news:publication_date>2026-06-27T23:17:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705624</loc>
  <lastmod>2026-06-27T23:17:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンパスで学ぶ磁気共鳴の教育実験（Exploring magnetic resonance with a compass）</news:title>
   <news:publication_date>2026-06-27T23:17:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705622</loc>
  <lastmod>2026-06-27T23:17:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間を取り込むニューラルネットワーク—スティグメルジーを用いた時間表現（Using stigmergy to incorporate the time into artificial neural networks）</news:title>
   <news:publication_date>2026-06-27T23:17:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705620</loc>
  <lastmod>2026-06-27T23:17:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多人数並列化でマンフォールド最適化を効率化する手法（Communication Efficient Parallel Algorithms for Optimization on Manifolds）</news:title>
   <news:publication_date>2026-06-27T23:17:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705618</loc>
  <lastmod>2026-06-27T22:25:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トロイダルネマティクスにおけるユリ型ねじれ分布（Lily-like twist distribution in toroidal nematics）</news:title>
   <news:publication_date>2026-06-27T22:25:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705616</loc>
  <lastmod>2026-06-27T22:17:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散信頼を促進するブロックチェーン活用の試み（PROMOTING DISTRIBUTED TRUST IN MACHINE LEARNING AND COMPUTATIONAL SIMULATION VIA A BLOCKCHAIN NETWORK）</news:title>
   <news:publication_date>2026-06-27T22:17:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705614</loc>
  <lastmod>2026-06-27T22:16:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TensorFlowとCUDA対応MPIによる分散DNN学習のスケーラブル化（Scalable Distributed DNN Training using TensorFlow and CUDA-Aware MPI: Characterization, Designs, and Performance Evaluation）</news:title>
   <news:publication_date>2026-06-27T22:16:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705612</loc>
  <lastmod>2026-06-27T22:16:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>劣化文書の二値化を強化する敵対的ノイズ・テクスチャ増強（IMPROVING DOCUMENT BINARIZATION VIA ADVERSARIAL NOISE-TEXTURE AUGMENTATION）</news:title>
   <news:publication_date>2026-06-27T22:16:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705610</loc>
  <lastmod>2026-06-27T22:16:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回帰におけるアンサンブル損失関数による頑健化（RELF: Robust Regression Extended with Ensemble Loss Function）</news:title>
   <news:publication_date>2026-06-27T22:16:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705608</loc>
  <lastmod>2026-06-27T22:15:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一観測から学べるガウス埋め込み（Provable Gaussian Embedding with One Observation）</news:title>
   <news:publication_date>2026-06-27T22:15:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705606</loc>
  <lastmod>2026-06-27T22:15:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>放射線画像のテクスチャを高速に合成する技術（RADIOMIC SYNTHESIS USING DEEP CONVOLUTIONAL NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-06-27T22:15:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705604</loc>
  <lastmod>2026-06-27T21:24:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低精度演算子の自動生成が切り開く現場適用の道（Automating Generation of Low Precision Deep Learning Operators）</news:title>
   <news:publication_date>2026-06-27T21:24:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705602</loc>
  <lastmod>2026-06-27T21:23:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配の一様収束と非凸学習の最適化（Uniform Convergence of Gradients for Non-Convex Learning and Optimization）</news:title>
   <news:publication_date>2026-06-27T21:23:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705600</loc>
  <lastmod>2026-06-27T21:23:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文法を教える敵対的分散（Teaching Syntax by Adversarial Distraction）</news:title>
   <news:publication_date>2026-06-27T21:23:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705598</loc>
  <lastmod>2026-06-27T21:22:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>退屈な宇宙論の「見えない差」を見分ける機械学習の力（On the dissection of degenerate cosmologies with machine learning）</news:title>
   <news:publication_date>2026-06-27T21:22:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705596</loc>
  <lastmod>2026-06-27T21:22:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複合視覚運動タスクのワンショット階層模倣学習（One-Shot Hierarchical Imitation Learning of Compound Visuomotor Tasks）</news:title>
   <news:publication_date>2026-06-27T21:22:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705594</loc>
  <lastmod>2026-06-27T21:22:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による異質な処置効果推定（Heterogeneous Treatment Effect Estimation through Deep Learning）</news:title>
   <news:publication_date>2026-06-27T21:22:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705592</loc>
  <lastmod>2026-06-27T21:21:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で標準宇宙論と修正重力モデルを見分ける（Distinguishing standard and modified gravity cosmologies with machine learning）</news:title>
   <news:publication_date>2026-06-27T21:21:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705590</loc>
  <lastmod>2026-06-27T20:30:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可逆的再帰型ニューラルネットワーク（Reversible Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-06-27T20:30:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705588</loc>
  <lastmod>2026-06-27T20:29:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチ正規化の効率化とサンプリング手法（Batch Normalization Sampling）</news:title>
   <news:publication_date>2026-06-27T20:29:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705586</loc>
  <lastmod>2026-06-27T20:28:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>力の位置不確実性下における最悪ケース構造解析の効率的サンプリング（EFFICIENT LOAD SAMPLING FOR WORST-CASE STRUCTURAL ANALYSIS UNDER FORCE LOCATION UNCERTAINTY）</news:title>
   <news:publication_date>2026-06-27T20:28:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705584</loc>
  <lastmod>2026-06-27T20:28:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>核ノルム正則化によるパネル回帰モデルの推定（Nuclear Norm Regularized Estimation of Panel Regression Models）</news:title>
   <news:publication_date>2026-06-27T20:28:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705582</loc>
  <lastmod>2026-06-27T20:28:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シグネチャモーメントによる確率過程の法則の特徴付け（Signature Moments to Characterize Laws of Stochastic Processes）</news:title>
   <news:publication_date>2026-06-27T20:28:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705580</loc>
  <lastmod>2026-06-27T20:27:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳表現のデコードとマルチモーダル学習（Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features）</news:title>
   <news:publication_date>2026-06-27T20:27:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705578</loc>
  <lastmod>2026-06-27T20:27:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的人口分布の高解像度生成（DeepDPM: Dynamic Population Mapping via Deep Neural Network）</news:title>
   <news:publication_date>2026-06-27T20:27:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705576</loc>
  <lastmod>2026-06-27T19:36:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソルに対するクロネッカー構造部分空間の一致検出（Tensor Matched Kronecker-Structured Subspace Detection for Missing Information）</news:title>
   <news:publication_date>2026-06-27T19:36:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705574</loc>
  <lastmod>2026-06-27T19:36:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間行動認識のハイパーパラメータ最適化に関する予備研究（A Preliminary Study on Hyperparameter Configuration for Human Activity Recognition）</news:title>
   <news:publication_date>2026-06-27T19:36:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705572</loc>
  <lastmod>2026-06-27T19:35:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分可変速度制限を深層強化学習で制御する研究（Differential Variable Speed Limits Control for Freeway Recurrent Bottlenecks via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-27T19:35:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705570</loc>
  <lastmod>2026-06-27T19:35:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アルツハイマー病の認知評価に関するVRとチューリング試験の応用（Cognitive Evaluation for the Diagnosis of Alzheimer’s Disease based on Turing Test and Virtual Environments）</news:title>
   <news:publication_date>2026-06-27T19:35:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705568</loc>
  <lastmod>2026-06-27T19:35:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン消費者レビューにおける両面（ツーサイド）議論の役割（Understanding the Role of Two-Sided Argumentation in Online Consumer Reviews: A Language-Based Perspective）</news:title>
   <news:publication_date>2026-06-27T19:35:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705566</loc>
  <lastmod>2026-06-27T19:35:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ないデータでも動く深層学習の現実（Learning Emotion from 100 Observations: Unexpected Robustness of Deep Learning under Strong Data Limitations）</news:title>
   <news:publication_date>2026-06-27T19:35:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705564</loc>
  <lastmod>2026-06-27T19:34:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>T-GANによる生成モデル訓練の新潮流（Training Generative Adversarial Networks Via Turing Test）</news:title>
   <news:publication_date>2026-06-27T19:34:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705562</loc>
  <lastmod>2026-06-27T18:43:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子チャネル学習と近似状態識別の効率的アルゴリズム（Sample Efficient Algorithms for Learning Quantum Channels in PAC Model and the Approximate State Discrimination Problem）</news:title>
   <news:publication_date>2026-06-27T18:43:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705560</loc>
  <lastmod>2026-06-27T18:43:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散領域における分類器回避の最小コスト保証（Evading Classifiers in Discrete Domains with Provable Optimality Guarantees）</news:title>
   <news:publication_date>2026-06-27T18:43:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705558</loc>
  <lastmod>2026-06-27T18:42:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HAR-Net: 深層表現と手作り特徴量を融合した人間行動認識（HAR-Net: Fusing Deep Representation and Hand-crafted Features for Human Activity Recognition）</news:title>
   <news:publication_date>2026-06-27T18:42:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705556</loc>
  <lastmod>2026-06-27T18:41:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語処理のためのベイズ圧縮（Bayesian Compression for Natural Language Processing）</news:title>
   <news:publication_date>2026-06-27T18:41:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705554</loc>
  <lastmod>2026-06-27T18:41:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い共分散轨道に基づく顔表情の自動解析（Automatic Analysis of Facial Expressions Based on Deep Covariance Trajectories）</news:title>
   <news:publication_date>2026-06-27T18:41:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705552</loc>
  <lastmod>2026-06-27T18:41:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡データに対するスーパーアンサンブル分類器（Superensemble Classifier for Improving Predictions in Imbalanced Datasets）</news:title>
   <news:publication_date>2026-06-27T18:41:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705550</loc>
  <lastmod>2026-06-27T18:41:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一の深度画像からの敵対的セマンティックシーン補完（Adversarial Semantic Scene Completion from a Single Depth Image）</news:title>
   <news:publication_date>2026-06-27T18:41:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705548</loc>
  <lastmod>2026-06-27T17:49:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>藻類の自動分類に関する研究（Investigating the Automatic Classification of Algae Using Fusion of Spectral and Morphological Characteristics of Algae via Deep Residual Learning）</news:title>
   <news:publication_date>2026-06-27T17:49:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705546</loc>
  <lastmod>2026-06-27T17:49:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重い裾の確率的線形バンディットに対するほぼ最適アルゴリズム（Almost Optimal Algorithms for Linear Stochastic Bandits with Heavy-Tailed Payoffs）</news:title>
   <news:publication_date>2026-06-27T17:49:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705544</loc>
  <lastmod>2026-06-27T17:49:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波形信号のエントロピーと圧縮に関する全館エネルギーデータの研究（Waveform Signal Entropy and Compression Study of Whole-Building Energy Datasets）</news:title>
   <news:publication_date>2026-06-27T17:49:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705542</loc>
  <lastmod>2026-06-27T17:48:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カウントデータの無向グラフィカルモデルの構造学習（Structure learning of undirected graphical models for count data）</news:title>
   <news:publication_date>2026-06-27T17:48:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705540</loc>
  <lastmod>2026-06-27T17:48:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短い発話に対する話者認証の補償（Short utterance compensation in speaker verification via cosine-based teacher-student learning of speaker embeddings）</news:title>
   <news:publication_date>2026-06-27T17:48:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705538</loc>
  <lastmod>2026-06-27T17:48:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロサービス、継続的アーキテクチャと技術的負債利息（Microservices, Continuous Architecture, and Technical Debt Interest: An Empirical Study）</news:title>
   <news:publication_date>2026-06-27T17:48:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705536</loc>
  <lastmod>2026-06-27T17:48:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANによるデータ拡張（GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-27T17:48:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705534</loc>
  <lastmod>2026-06-27T16:56:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異常から正常への翻訳による医用画像合成と病変検出（An Adversarial Learning Approach to Medical Image Synthesis for Lesion Detection）</news:title>
   <news:publication_date>2026-06-27T16:56:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705532</loc>
  <lastmod>2026-06-27T16:56:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>株価のジャンプ到来予測と新しい注意機構付きネットワーク（Forecasting of Jump Arrivals in Stock Prices: New Attention-based Network Architecture using Limit Order Book Data）</news:title>
   <news:publication_date>2026-06-27T16:56:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705530</loc>
  <lastmod>2026-06-27T16:55:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>格子緩和が相転移へ与える影響：機械学習ポテンシャルによる高エントロピー合金の研究 (Impact of lattice relaxations on phase transitions in a high-entropy alloy studied by machine-learning potentials)</news:title>
   <news:publication_date>2026-06-27T16:55:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705528</loc>
  <lastmod>2026-06-27T16:54:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンパクトな語義セグメンテーションモデルの高速NAS（Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells）</news:title>
   <news:publication_date>2026-06-27T16:54:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705526</loc>
  <lastmod>2026-06-27T16:54:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイキング神経回路で実現する適応的運動制御と学習（Adaptive motor control and learning in a spiking neural network realised on a mixed-signal neuromorphic processor）</news:title>
   <news:publication_date>2026-06-27T16:54:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705524</loc>
  <lastmod>2026-06-27T16:54:23Z</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・シーケンス変換における潜在分節とオンライン生成（Neural Sequence Transduction with Latent Segmentation）</news:title>
   <news:publication_date>2026-06-27T16:54:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705522</loc>
  <lastmod>2026-06-27T16:54:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変化する環境下で最適なオンライン学習を実現する手法（Adaptive Online Learning in Dynamic Environments）</news:title>
   <news:publication_date>2026-06-27T16:54:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705520</loc>
  <lastmod>2026-06-27T16:02:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワークをガウス過程の視点で見る（A Gaussian Process perspective on Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-27T16:02:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705518</loc>
  <lastmod>2026-06-27T16:01:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フラッシュX線単一粒子回折イメージングの教師あり分類手法（SUPERVISED CLASSIFICATION METHODS FOR FLASH X-RAY SINGLE PARTICLE DIFFRACTION IMAGING）</news:title>
   <news:publication_date>2026-06-27T16:01:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705516</loc>
  <lastmod>2026-06-27T16:01:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知覚に基づく視覚対話型学習の再設計（Perceptual Visual Interactive Learning）</news:title>
   <news:publication_date>2026-06-27T16:01:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705514</loc>
  <lastmod>2026-06-27T16:01:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的に頑健なガウス過程最適化（Adversarially Robust Optimization with Gaussian Processes）</news:title>
   <news:publication_date>2026-06-27T16:01:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705512</loc>
  <lastmod>2026-06-27T16:01:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語が数学の学びを変える（The Role of Language in Teaching and Learning Mathematics）</news:title>
   <news:publication_date>2026-06-27T16:01:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705510</loc>
  <lastmod>2026-06-27T16:00:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共分散推定によるRBMの効率的学習（EFFICIENT LEARNING OF RESTRICTED BOLTZMANN MACHINES USING COVARIANCE ESTIMATES）</news:title>
   <news:publication_date>2026-06-27T16:00:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705508</loc>
  <lastmod>2026-06-27T16:00:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可分化Bregman発散から導かれる計量に基づく幾何とクラスタリング（Geometry and clustering with metrics derived from separable Bregman divergences）</news:title>
   <news:publication_date>2026-06-27T16:00:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705506</loc>
  <lastmod>2026-06-27T15:08:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>キーワードで“話者だけ”を強調する音声分離技術（SPEAKER SELECTIVE BEAMFORMER WITH KEYWORD MASK ESTIMATION）</news:title>
   <news:publication_date>2026-06-27T15:08:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705504</loc>
  <lastmod>2026-06-27T15:01:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>法と敵対的機械学習（Law and Adversarial Machine Learning）</news:title>
   <news:publication_date>2026-06-27T15:01:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705502</loc>
  <lastmod>2026-06-27T15:01:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>偽ノード攻撃が明かすGCNの脆弱性（Fake Node Attacks on Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-06-27T15:01:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705500</loc>
  <lastmod>2026-06-27T15:00:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Word Embedding based Edit Distance（Word Embedding based Edit Distance）</news:title>
   <news:publication_date>2026-06-27T15:00:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705498</loc>
  <lastmod>2026-06-27T14:59:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>主成分分析に基づく量子データ圧縮（Quantum data compression by principal component analysis）</news:title>
   <news:publication_date>2026-06-27T14:59:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705496</loc>
  <lastmod>2026-06-27T14:59:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲート付きRNNから学ぶ解釈可能な構造（Learning with Interpretable Structure from Gated RNN）</news:title>
   <news:publication_date>2026-06-27T14:59:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705494</loc>
  <lastmod>2026-06-27T14:59:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ない追加パラメータで複数タスクを効率化する手法（FOR THE PRICE OF 1: PARAMETER-EFFICIENT MULTI-TASK AND TRANSFER LEARNING）</news:title>
   <news:publication_date>2026-06-27T14:59:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705492</loc>
  <lastmod>2026-06-27T14:07:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>直線的に学ぶ辞書学習：サブグラデイント法が示す実用的回復性（Subgradient Descent Learns Orthogonal Dictionaries）</news:title>
   <news:publication_date>2026-06-27T14:07:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705490</loc>
  <lastmod>2026-06-27T14:07:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>東アフリカの現場が求めた機械学習研究一覧（Some Requests for Machine Learning Research from the East African Tech Scene）</news:title>
   <news:publication_date>2026-06-27T14:07:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705488</loc>
  <lastmod>2026-06-27T14:07:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフラプラシアンのスペクトルを深掘りするスペクトル埋め込みノルム（Spectral Embedding Norm: Looking Deep into the Spectrum of the Graph Laplacian）</news:title>
   <news:publication_date>2026-06-27T14:07:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705486</loc>
  <lastmod>2026-06-27T14:06:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>口腔疾患の機械学習による自動化と全身健康との相関（Automated Process Incorporating Machine Learning Segmentation and Correlation of Oral Diseases with Systemic Health）</news:title>
   <news:publication_date>2026-06-27T14:06:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705484</loc>
  <lastmod>2026-06-27T14:06:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トランケーテッド逆伝播による双層最適化（Truncated Back-propagation for Bilevel Optimization）</news:title>
   <news:publication_date>2026-06-27T14:06:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705482</loc>
  <lastmod>2026-06-27T14:06:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SpiderBoostとMomentumによる高速な確率的分散削減アルゴリズム（SpiderBoost and Momentum: Faster Stochastic Variance Reduction Algorithms）</news:title>
   <news:publication_date>2026-06-27T14:06:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705480</loc>
  <lastmod>2026-06-27T14:05:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DNAコンピューティングに学ぶニューラルネットワーク構造探索（Structure Learning of Deep Networks via DNA Computing Algorithm）</news:title>
   <news:publication_date>2026-06-27T14:05:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705478</loc>
  <lastmod>2026-06-27T13:14:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ畳み込みネットワークによる組合せ最適化と誘導木探索（Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search）</news:title>
   <news:publication_date>2026-06-27T13:14:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705476</loc>
  <lastmod>2026-06-27T13:14:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像質問への理解・構成・応答（Understand, Compose and Respond - Answering Visual Questions by a Composition of Abstract Procedures）</news:title>
   <news:publication_date>2026-06-27T13:14:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705474</loc>
  <lastmod>2026-06-27T13:14:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スポーツ映像の単一フレームからのカメラ較正（Sports Camera Calibration via Synthetic Data）</news:title>
   <news:publication_date>2026-06-27T13:14:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705472</loc>
  <lastmod>2026-06-27T13:13:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタモデリングと深層強化学習による界面粘着則の自動発見（Meta-modeling game for deriving theoretical-consistent, micro-structural-based traction-separation laws via deep reinforcement learning）</news:title>
   <news:publication_date>2026-06-27T13:13:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705470</loc>
  <lastmod>2026-06-27T13:13:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンドフィードバックによる効率的ルーティング学習（Learning to Route Efficiently with End-to-End Feedback: The Value of Networked Structure）</news:title>
   <news:publication_date>2026-06-27T13:13:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705468</loc>
  <lastmod>2026-06-27T13:13:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体の非把持操作を効率的に学ぶための計画的初期状態導入（Learning with Planned Episodic Resets）</news:title>
   <news:publication_date>2026-06-27T13:13:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705466</loc>
  <lastmod>2026-06-27T13:13:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストリーミンググラフニューラルネットワーク（Streaming Graph Neural Networks）</news:title>
   <news:publication_date>2026-06-27T13:13:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705464</loc>
  <lastmod>2026-06-27T12:22:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース化フロントエンドによる頑健な敵対的学習（Robust Adversarial Learning via Sparsifying Front Ends）</news:title>
   <news:publication_date>2026-06-27T12:22:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705462</loc>
  <lastmod>2026-06-27T12:21:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続学習における生成モデルを用いた分類学習（Continual Classification Learning Using Generative Models）</news:title>
   <news:publication_date>2026-06-27T12:21:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705460</loc>
  <lastmod>2026-06-27T12:21:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>密度整合によるスピン模型のループ補正（Loop corrections in spin models through density consistency）</news:title>
   <news:publication_date>2026-06-27T12:21:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705458</loc>
  <lastmod>2026-06-27T12:21:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己正規化マルチンゲールの集中不等式に関する新知見 (NEW INSIGHTS ON CONCENTRATION INEQUALITIES FOR SELF-NORMALIZED MARTINGALES)</news:title>
   <news:publication_date>2026-06-27T12:21:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705456</loc>
  <lastmod>2026-06-27T12:20:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビデオゲームにおける逆強化学習の拡張（Inverse reinforcement learning for video games）</news:title>
   <news:publication_date>2026-06-27T12:20:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705454</loc>
  <lastmod>2026-06-27T12:20:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成モデルによる量子状態再構築（Reconstructing quantum states with generative models）</news:title>
   <news:publication_date>2026-06-27T12:20:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705452</loc>
  <lastmod>2026-06-27T12:20:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スピーカー非依存のリップリーディング機械調査（The speaker-independent lipreading play-off; a survey of lipreading machines）</news:title>
   <news:publication_date>2026-06-27T12:20:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705450</loc>
  <lastmod>2026-06-27T11:29:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウド量子コンピュータ上でのアルゴリズム展開フレームワーク（A framework for algorithm deployment on cloud-based quantum computers）</news:title>
   <news:publication_date>2026-06-27T11:29:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705448</loc>
  <lastmod>2026-06-27T11:28:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構を用いたハイパースペクトル帯域選択（Attention-based CNNs for Hyperspectral Band Selection）</news:title>
   <news:publication_date>2026-06-27T11:28:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705446</loc>
  <lastmod>2026-06-27T11:27:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>母集団レベルの原因分布を推定する正則化ベイズ転移学習（Regularized Bayesian transfer learning for population-level etiological distributions）</news:title>
   <news:publication_date>2026-06-27T11:27:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705444</loc>
  <lastmod>2026-06-27T11:26:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パッチベースの干渉位相推定（Patch-based Interferometric Phase Estimation via Mixture of Gaussian Density Modelling &amp;amp; Non-local Averaging in the Complex Domain）</news:title>
   <news:publication_date>2026-06-27T11:26:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705442</loc>
  <lastmod>2026-06-27T11:26:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床概念抽出における文脈的単語埋め込み（Clinical Concept Extraction with Contextual Word Embedding）</news:title>
   <news:publication_date>2026-06-27T11:26:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705440</loc>
  <lastmod>2026-06-27T11:26:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限体と応用における発見学習の授業設計（DISCOVERY LEARNING IN AN INTERDISCIPLINARY COURSE ON FINITE FIELDS AND APPLICATIONS）</news:title>
   <news:publication_date>2026-06-27T11:26:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705438</loc>
  <lastmod>2026-06-27T11:26:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠方X線クラスターにおける分子ガス量の環境依存性の解明 (Revealing environmental dependence of molecular gas content in a distant X-ray cluster at z = 2.51)</news:title>
   <news:publication_date>2026-06-27T11:26:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705436</loc>
  <lastmod>2026-06-27T10:34:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多言語・多表現のマルチビュー学習によるエンティティ型推定（Multi-Multi-View Learning: Multilingual and Multi-Representation Entity Typing）</news:title>
   <news:publication_date>2026-06-27T10:34:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705434</loc>
  <lastmod>2026-06-27T10:25:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近傍合意ネットワークによる密対応の学習（Neighbourhood Consensus Networks）</news:title>
   <news:publication_date>2026-06-27T10:25:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705432</loc>
  <lastmod>2026-06-27T10:25:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度4K/8K映像に対する高速で高精度な物体検出（Fast and accurate object detection in high resolution 4K and 8K video using GPUs）</news:title>
   <news:publication_date>2026-06-27T10:25:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705430</loc>
  <lastmod>2026-06-27T10:24:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>矮小銀河の星間物質を機械学習で解く（The interstellar medium of dwarf galaxies: new insights from Machine Learning analysis of emission line spectra）</news:title>
   <news:publication_date>2026-06-27T10:24:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705428</loc>
  <lastmod>2026-06-27T10:24:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分量子状態の対角化（Variational Quantum State Diagonalization）</news:title>
   <news:publication_date>2026-06-27T10:24:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705426</loc>
  <lastmod>2026-06-27T10:23:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>睡眠様スローオシレーションが視覚分類を改善する仕組み（Sleep-like slow oscillations improve visual classification through synaptic homeostasis and memory association in a thalamo-cortical model）</news:title>
   <news:publication_date>2026-06-27T10:23:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705424</loc>
  <lastmod>2026-06-27T10:23:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>詩の作者分類に関するテキスト分類研究（Poetry Authorship Classification）</news:title>
   <news:publication_date>2026-06-27T10:23:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705422</loc>
  <lastmod>2026-06-27T09:32:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別化された疾病軌跡の予測（Forecasting Individualized Disease Trajectories using Interpretable Deep Learning）</news:title>
   <news:publication_date>2026-06-27T09:32:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705420</loc>
  <lastmod>2026-06-27T09:32:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>降水ナウキャスティング：双方向LSTMと1次元CNNの活用 (Precipitation Nowcasting: Leveraging bidirectional LSTM and 1D CNN)</news:title>
   <news:publication_date>2026-06-27T09:32:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705418</loc>
  <lastmod>2026-06-27T09:31:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多段階近似を使った雑音下のブラックボックス最適化（Noisy Blackbox Optimization with Multi-Fidelity Queries: A Tree Search Approach）</news:title>
   <news:publication_date>2026-06-27T09:31:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705416</loc>
  <lastmod>2026-06-27T09:30:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>流体メタンの状態方程式と機械学習ポテンシャル（Equation of state of fluid methane from first principles with machine learning potentials）</news:title>
   <news:publication_date>2026-06-27T09:30:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705414</loc>
  <lastmod>2026-06-27T09:30:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合高次仮想要素法の基礎部品：射影作用素と微分作用素（Bricks for the mixed high-order virtual element method: projectors and differential operators）</news:title>
   <news:publication_date>2026-06-27T09:30:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705412</loc>
  <lastmod>2026-06-27T09:30:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>選択分析における深層ニューラルネットワーク（Deep Neural Networks for Choice Analysis: A Statistical Learning Theory Perspective）</news:title>
   <news:publication_date>2026-06-27T09:30:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705410</loc>
  <lastmod>2026-06-27T09:29:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交差点における車同士の交渉行動の学習（Learning Negotiating Behavior Between Cars in Intersections using Deep Q-Learning）</news:title>
   <news:publication_date>2026-06-27T09:29:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705408</loc>
  <lastmod>2026-06-27T08:38:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>微小循環画像からの敗血症判別を目指す機械学習（Machine Learning Algorithms for Classification of Microcirculation Images from Septic and Non-Septic Patients）</news:title>
   <news:publication_date>2026-06-27T08:38:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705406</loc>
  <lastmod>2026-06-27T08:38:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データがモデル構築と予測で果たす役割（The Role of Data in Model Building and Prediction: A Survey Through Examples）</news:title>
   <news:publication_date>2026-06-27T08:38:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705404</loc>
  <lastmod>2026-06-27T08:37:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>性能最適化した生徒モデルによる蒸留（Distilling with Performance Enhanced Students）</news:title>
   <news:publication_date>2026-06-27T08:37:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705402</loc>
  <lastmod>2026-06-27T08:37:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UAV画像向け高解像度セマンティックセグメンテーションデータセット「UAVid」（UAVid: A Semantic Segmentation Dataset for UAV Imagery）</news:title>
   <news:publication_date>2026-06-27T08:37:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705400</loc>
  <lastmod>2026-06-27T08:36:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Transformerを用いた変分半教師付きアスペクト項目感情分析（Variational Semi-supervised Aspect-term Sentiment Analysis via Transformer）</news:title>
   <news:publication_date>2026-06-27T08:36:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705398</loc>
  <lastmod>2026-06-27T08:36:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタデータを使い分ける地図方程式（A Map Equation with Metadata: Varying the Role of Attributes in Community Detection）</news:title>
   <news:publication_date>2026-06-27T08:36:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705396</loc>
  <lastmod>2026-06-27T08:36:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車車間通信における効率的な情報伝播のための深層学習アプローチ（A Deep Learning Approach to Efficient Information Dissemination in Vehicular Floating Content）</news:title>
   <news:publication_date>2026-06-27T08:36:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705394</loc>
  <lastmod>2026-06-27T07:44:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地下多相流の縮約モデル化とDR-RNNによる高速近似（Reduced order modeling of subsurface multiphase flow models using deep residual recurrent neural networks）</news:title>
   <news:publication_date>2026-06-27T07:44:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705392</loc>
  <lastmod>2026-06-27T07:44:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>双方向テレオペレーションによるスクーピング動作の深層学習（Deep Learning Scooping Motion using Bilateral Teleoperations）</news:title>
   <news:publication_date>2026-06-27T07:44:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705390</loc>
  <lastmod>2026-06-27T07:43:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UAVネットワークにおけるマルチエージェント強化学習による資源配分（Multi-Agent Reinforcement Learning Based Resource Allocation for UAV Networks）</news:title>
   <news:publication_date>2026-06-27T07:43:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705388</loc>
  <lastmod>2026-06-27T07:43:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GBDTの速度ベンチマークが皆間違っている理由（Why every GBDT speed benchmark is wrong）</news:title>
   <news:publication_date>2026-06-27T07:43:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705386</loc>
  <lastmod>2026-06-27T07:42:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像として扱う自然言語理解（Image-based Natural Language Understanding Using 2D Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-27T07:42:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705384</loc>
  <lastmod>2026-06-27T07:42:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロヘキサキャビティピクセル検出器の動作と性能（Operation and Performance of Microhexcavity Pixel Detector in Gas Discharge and Avalanche Mode）</news:title>
   <news:publication_date>2026-06-27T07:42:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705382</loc>
  <lastmod>2026-06-27T07:42:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CatBoost: カテゴリ変数対応の勾配ブースティング（CatBoost: gradient boosting with categorical features）</news:title>
   <news:publication_date>2026-06-27T07:42:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705380</loc>
  <lastmod>2026-06-27T06:51:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散領域におけるスパースガウス過程（Sparse Gaussian Processes on Discrete Domains）</news:title>
   <news:publication_date>2026-06-27T06:51:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705378</loc>
  <lastmod>2026-06-27T06:51:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中国電力システムの脱炭素における水力・蓄電・送電の役割（The role of hydro power, storage and transmission in the decarbonization of the Chinese power system）</news:title>
   <news:publication_date>2026-06-27T06:51:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705376</loc>
  <lastmod>2026-06-27T06:50:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>G-SMOTEによる不均衡学習の高次元合成少数オーバーサンプリング（G-SMOTE: A GMM-BASED SYNTHETIC MINORITY OVERSAMPLING TECHNIQUE FOR IMBALANCED LEARNING）</news:title>
   <news:publication_date>2026-06-27T06:50:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705374</loc>
  <lastmod>2026-06-27T06:50:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベル比率から個別ラベルを復元するためのラベル伝播法（Label Propagation for Learning with Label Proportions）</news:title>
   <news:publication_date>2026-06-27T06:50:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705372</loc>
  <lastmod>2026-06-27T06:49:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外部情報のノイズを見抜く学習法（Learning to Discriminate Noises for Incorporating External Information in Neural Machine Translation）</news:title>
   <news:publication_date>2026-06-27T06:49:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705370</loc>
  <lastmod>2026-06-27T06:49:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人工ニューラルネットワークによる量子計算のエミュレーション（Emulating quantum computation with artificial neural networks）</news:title>
   <news:publication_date>2026-06-27T06:49:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705368</loc>
  <lastmod>2026-06-27T06:49:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3DコーンビームCTにおける歯科病変検出（Dental pathology detection in 3D cone-beam CT）</news:title>
   <news:publication_date>2026-06-27T06:49:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705366</loc>
  <lastmod>2026-06-27T05:57:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間中心サイバーフィジカルシステムにおけるセグメンテーション解析（Segmentation Analysis in Human Centric Cyber-Physical Systems using Graphical Lasso）</news:title>
   <news:publication_date>2026-06-27T05:57:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705364</loc>
  <lastmod>2026-06-27T05:57:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成画像の色空間適応で実画像セグメンテーションを改善する手法（Learning Color Space Adaptation from Synthetic to Real Images of Cirrus Clouds）</news:title>
   <news:publication_date>2026-06-27T05:57:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705362</loc>
  <lastmod>2026-06-27T05:56:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数データで学習する音声分類器の訓練（TRAINING NEURAL AUDIO CLASSIFIERS WITH FEW DATA）</news:title>
   <news:publication_date>2026-06-27T05:56:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705360</loc>
  <lastmod>2026-06-27T05:56:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト誘導型ランキングネットワークによる注意機構付き画像リツイート予測（Textually Guided Ranking Network for Attentional Image Retweet Modeling）</news:title>
   <news:publication_date>2026-06-27T05:56:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705358</loc>
  <lastmod>2026-06-27T05:56:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>道路ネットワークにおけるマルチステップ速度予測（Multistep Speed Prediction on Traffic Networks: A Graph Convolutional Sequence-to-Sequence Learning Approach with Attention Mechanism）</news:title>
   <news:publication_date>2026-06-27T05:56:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705356</loc>
  <lastmod>2026-06-27T05:55:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車載向けフローティングコンテンツ管理に対する深層学習戦略（A Deep Learning Strategy for Vehicular Floating Content Management）</news:title>
   <news:publication_date>2026-06-27T05:55:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705354</loc>
  <lastmod>2026-06-27T05:55:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コードスイッチを学習するデータ増強法（LEARN TO CODE-SWITCH: DATA AUGMENTATION USING COPY MECHANISM ON LANGUAGE MODELING）</news:title>
   <news:publication_date>2026-06-27T05:55:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705352</loc>
  <lastmod>2026-06-27T05:04:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱凸弱凹ミンマックス問題に対する一階収束理論（First-order Convergence Theory for Weakly-Convex-Weakly-Concave Min-max Problems）</news:title>
   <news:publication_date>2026-06-27T05:04:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705350</loc>
  <lastmod>2026-06-27T05:04:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DSFD: Dual Shot Face Detector（DSFD: Dual Shot Face Detector）</news:title>
   <news:publication_date>2026-06-27T05:04:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705348</loc>
  <lastmod>2026-06-27T05:03:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブワードでULMFiTを多層化する意義（Universal Language Model Fine-Tuning with Subword Tokenization for Polish）</news:title>
   <news:publication_date>2026-06-27T05:03:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705346</loc>
  <lastmod>2026-06-27T05:03:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PN接合の粒子シミュレーションにおけるポアソン方程式の深層学習による解法（Solving Poisson’s Equation using Deep Learning in Particle Simulation of PN Junction）</news:title>
   <news:publication_date>2026-06-27T05:03:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705344</loc>
  <lastmod>2026-06-27T05:03:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層表現を活用したニューラル機械翻訳の改良（Exploiting Deep Representations for Neural Machine Translation）</news:title>
   <news:publication_date>2026-06-27T05:03:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705342</loc>
  <lastmod>2026-06-27T05:03:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粒子凝集型バイオセンサーの高スループット解析を可能にする深層学習とホログラフィー（Deep learning enables high-throughput analysis of particle-aggregation-based bio-sensors imaged using holography）</news:title>
   <news:publication_date>2026-06-27T05:03:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705340</loc>
  <lastmod>2026-06-27T05:03:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚と触覚を「同時に学ぶ」ことで接触を伴う作業が劇的に効率化する（Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks）</news:title>
   <news:publication_date>2026-06-27T05:03:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705338</loc>
  <lastmod>2026-06-27T04:11:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習された最適化器の訓練における病理の理解と是正（Understanding and correcting pathologies in the training of learned optimizers）</news:title>
   <news:publication_date>2026-06-27T04:11:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705336</loc>
  <lastmod>2026-06-27T04:11:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模知識ベースからの検索のためのテキスト埋め込み（Text Embeddings for Retrieval from a Large Knowledge Base）</news:title>
   <news:publication_date>2026-06-27T04:11:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705334</loc>
  <lastmod>2026-06-27T04:11:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン映画知識ライブラリに基づくデータ駆動型ブロックバスター企画（Data-driven Blockbuster Planning on Online Movie Knowledge Library）</news:title>
   <news:publication_date>2026-06-27T04:11:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705332</loc>
  <lastmod>2026-06-27T04:10:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸・非滑らかなスパース最適化の適応的反復再重み付け法（Nonconvex and Nonsmooth Sparse Optimization via Adaptively Iterative Reweighted Methods）</news:title>
   <news:publication_date>2026-06-27T04:10:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705330</loc>
  <lastmod>2026-06-27T04:10:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化勾配ブースティング機械（Randomized Gradient Boosting Machine）</news:title>
   <news:publication_date>2026-06-27T04:10:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705328</loc>
  <lastmod>2026-06-27T04:10:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長短期記憶を用いた時系列予測の深層学習的アプローチ（Deep Learning with Long Short-Term Memory for Time Series Prediction）</news:title>
   <news:publication_date>2026-06-27T04:10:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705326</loc>
  <lastmod>2026-06-27T04:09:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>窒化物半導体のバンドギャップ・バンド整合の機械学習予測（Band gap and band alignment prediction of nitride based semiconductors using machine learning）</news:title>
   <news:publication_date>2026-06-27T04:09:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705324</loc>
  <lastmod>2026-06-27T03:19:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファッション属性検出のための深層学習モデル（A Deep-Learning-Based Fashion Attributes Detection Model）</news:title>
   <news:publication_date>2026-06-27T03:19:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705322</loc>
  <lastmod>2026-06-27T03:18:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FewRelをめぐる実務的解説—大規模少ショット関係分類データセット（FewRel: A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation）</news:title>
   <news:publication_date>2026-06-27T03:18:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705320</loc>
  <lastmod>2026-06-27T03:18:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>認知無線ベースのブロックチェーンネットワークにおける取引伝送とチャネル選択の共同最適化（JOINT TRANSACTION TRANSMISSION AND CHANNEL SELECTION IN COGNITIVE RADIO BASED BLOCKCHAIN NETWORKS: A DEEP REINFORCEMENT LEARNING APPROACH）</news:title>
   <news:publication_date>2026-06-27T03:18:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705318</loc>
  <lastmod>2026-06-27T03:18:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語埋め込みの局所ホモロジー（Local Homology of Word Embeddings）</news:title>
   <news:publication_date>2026-06-27T03:18:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705316</loc>
  <lastmod>2026-06-27T03:18:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平滑化された回帰とLQR制御のためのオンラインアルゴリズム（An Online Algorithm for Smoothed Regression and LQR Control）</news:title>
   <news:publication_date>2026-06-27T03:18:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705314</loc>
  <lastmod>2026-06-27T03:17:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付きK平均クラスタリングへの2値最適化アプローチ（A Binary Optimization Approach for Constrained K-Means Clustering）</news:title>
   <news:publication_date>2026-06-27T03:17:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705312</loc>
  <lastmod>2026-06-27T03:17:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エリア注意機構が変える注意の粒度（Area Attention）</news:title>
   <news:publication_date>2026-06-27T03:17:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705310</loc>
  <lastmod>2026-06-27T02:26:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>nGraph-HEによる同型暗号下での深層学習コンパイラ（nGraph-HE: A Graph Compiler for Deep Learning on Homomorphically Encrypted Data）</news:title>
   <news:publication_date>2026-06-27T02:26:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705308</loc>
  <lastmod>2026-06-27T02:26:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fisherカーネルによるブラックボックス予測の解釈（Interpreting Black Box Predictions using Fisher Kernels）</news:title>
   <news:publication_date>2026-06-27T02:26:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705306</loc>
  <lastmod>2026-06-27T02:26:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PoPPy: PyTorchベースの点過程ツールボックス（PoPPy: A Point Process Toolbox Based on PyTorch）</news:title>
   <news:publication_date>2026-06-27T02:26:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705304</loc>
  <lastmod>2026-06-27T02:25:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークにおける意味表現の数学理論（A mathematical theory of semantic development in deep neural networks）</news:title>
   <news:publication_date>2026-06-27T02:25:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705302</loc>
  <lastmod>2026-06-27T02:25:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓MRIからのエンドツーエンド診断とセグメンテーション学習（End-to-End Diagnosis and Segmentation Learning from Cardiac Magnetic Resonance Imaging）</news:title>
   <news:publication_date>2026-06-27T02:25:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705300</loc>
  <lastmod>2026-06-27T02:25:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>損失のある観測からの生成モデル再現（Reproducing AmbientGAN: Generative models from lossy measurements）</news:title>
   <news:publication_date>2026-06-27T02:25:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705298</loc>
  <lastmod>2026-06-27T02:25:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習ベースの逆問題解法：肺EITのシミュレーション研究（A Learning-Based Method for Solving Ill-Posed Nonlinear Inverse Problems: A Simulation Study of Lung EIT）</news:title>
   <news:publication_date>2026-06-27T02:25:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705296</loc>
  <lastmod>2026-06-27T01:33:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Autowarpによる時系列類似度の自動学習（Autowarp: Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders）</news:title>
   <news:publication_date>2026-06-27T01:33:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705294</loc>
  <lastmod>2026-06-27T01:32:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重なり合う銀河のデブレンディングにおける分岐型生成対抗ネットワーク（Deblending galaxy superpositions with branched generative adversarial networks）</news:title>
   <news:publication_date>2026-06-27T01:32:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705292</loc>
  <lastmod>2026-06-27T01:32:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルフリー階層的強化学習における表現学習（Learning Representations in Model-Free Hierarchical Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-27T01:32:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705290</loc>
  <lastmod>2026-06-27T01:32:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NestDNNによるリソース対応型マルチテナント端末上深層学習（NestDNN: Resource-Aware Multi-Tenant On-Device Deep Learning for Continuous Mobile Vision）</news:title>
   <news:publication_date>2026-06-27T01:32:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705288</loc>
  <lastmod>2026-06-27T01:31:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小二乗における早期停止の連続時間的考察 (A Continuous-Time View of Early Stopping for Least Squares)</news:title>
   <news:publication_date>2026-06-27T01:31:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705286</loc>
  <lastmod>2026-06-27T01:31:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非負値行列因子分解のモデル選択（Model Selection for Nonnegative Matrix Factorization by Support Union Recovery）</news:title>
   <news:publication_date>2026-06-27T01:31:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705284</loc>
  <lastmod>2026-06-27T01:31:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>成人の国勢調査データによる所得階層予測の統計的アプローチ（A Statistical Approach to Adult Census Income Level Prediction）</news:title>
   <news:publication_date>2026-06-27T01:31:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705282</loc>
  <lastmod>2026-06-27T00:40:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランクテンソル分解の統計力学的分析（Statistical mechanics of low-rank tensor decomposition）</news:title>
   <news:publication_date>2026-06-27T00:40:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705280</loc>
  <lastmod>2026-06-27T00:40:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ類似度の畳み込み的集合照合（Convolutional Set Matching for Graph Similarity）</news:title>
   <news:publication_date>2026-06-27T00:40:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705278</loc>
  <lastmod>2026-06-27T00:39:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無効結果の価値――物理教育研究における「何も起きなかった」ことの意味（Nothing’s plenty: The significance of null results in physics education research）</news:title>
   <news:publication_date>2026-06-27T00:39:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705276</loc>
  <lastmod>2026-06-27T00:39:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Graph Laplacian Mixture Modelの解説（Graph Laplacian Mixture Model）</news:title>
   <news:publication_date>2026-06-27T00:39:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705274</loc>
  <lastmod>2026-06-27T00:38:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で量子デバイスの計測を効率化する手法（Efficiently measuring a quantum device using machine learning）</news:title>
   <news:publication_date>2026-06-27T00:38:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705272</loc>
  <lastmod>2026-06-27T00:38:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NormADに基づく多層スパイキングニューラルネットワークの学習（TRAINING MULTI-LAYER SPIKING NEURAL NETWORKS USING NORMAD BASED SPATIO-TEMPORAL ERROR BACKPROPAGATION）</news:title>
   <news:publication_date>2026-06-27T00:38:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705270</loc>
  <lastmod>2026-06-27T00:38:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似的な二乗輸送距離をほぼ線形時間で計算する手法（Approximating the Quadratic Transportation Metric in Near-Linear Time）</news:title>
   <news:publication_date>2026-06-27T00:38:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705268</loc>
  <lastmod>2026-06-26T23:47:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単層・多層フィードフォワードニューラルネットワークの近似に関する負の結果（NEGATIVE RESULTS FOR APPROXIMATION USING SINGLE LAYER AND MULTILAYER FEEDFORWARD NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-06-26T23:47:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705266</loc>
  <lastmod>2026-06-26T23:47:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レーザー照明画像のスペックルノイズ低減を学ぶ（DeepLSR: a deep learning approach for laser speckle reduction）</news:title>
   <news:publication_date>2026-06-26T23:47:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705264</loc>
  <lastmod>2026-06-26T23:46:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情認識の深層化と可視化：EmotionalDANによる顔ランドマーク統合学習（Classifying and Visualizing Emotions with Emotional DAN）</news:title>
   <news:publication_date>2026-06-26T23:46:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705262</loc>
  <lastmod>2026-06-26T23:45:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスター環境で小型の星形成銀河が急速に消光するメカニズム（Compact star-forming galaxies preferentially quenched to become PSBs in z &amp;lt; 1 clusters）</news:title>
   <news:publication_date>2026-06-26T23:45:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705260</loc>
  <lastmod>2026-06-26T23:45:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延する作業者（Straggler）を許容する分散学習の計算スケジューリング（Computation Scheduling for Distributed Machine Learning with Straggling Workers）</news:title>
   <news:publication_date>2026-06-26T23:45:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705258</loc>
  <lastmod>2026-06-26T23:45:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ畳み込みエンコーダによる構造化データからのテキスト生成（Deep Graph Convolutional Encoders for Structured Data to Text Generation）</news:title>
   <news:publication_date>2026-06-26T23:45:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705256</loc>
  <lastmod>2026-06-26T23:45:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的代替学習によるグラデーション隠蔽への攻撃（Stochastic Substitute Training）</news:title>
   <news:publication_date>2026-06-26T23:45:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705254</loc>
  <lastmod>2026-06-26T22:53:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタ学習によるマルチタスク通信（META-LEARNING MULTI-TASK COMMUNICATION）</news:title>
   <news:publication_date>2026-06-26T22:53:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705252</loc>
  <lastmod>2026-06-26T22:53:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイキングニューラルネットワークによる低消費電力強化学習（Learning First-to-Spike Policies for Neuromorphic Control Using Policy Gradients）</news:title>
   <news:publication_date>2026-06-26T22:53:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705250</loc>
  <lastmod>2026-06-26T22:53:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分集合の好みによる能動ランキング（Active Ranking with Subset-wise Preferences）</news:title>
   <news:publication_date>2026-06-26T22:53:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705248</loc>
  <lastmod>2026-06-26T22:52:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>矮小銀河の低金属間質（Dwarf Galaxies: Their Low Metallicity Interstellar Medium）</news:title>
   <news:publication_date>2026-06-26T22:52:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705246</loc>
  <lastmod>2026-06-26T22:52:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注文板データから価格予測へ──非定常性を克服する特徴設計（Using Deep Learning for price prediction by exploiting stationary limit order book features）</news:title>
   <news:publication_date>2026-06-26T22:52:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705244</loc>
  <lastmod>2026-06-26T22:52:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GhostVLADによる集合ベース顔認証の要点整理（GhostVLAD for set-based face recognition）</news:title>
   <news:publication_date>2026-06-26T22:52:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705242</loc>
  <lastmod>2026-06-26T22:52:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>λリターンとエクスペリエンスリプレイの調和（Reconciling λ-Returns with Experience Replay）</news:title>
   <news:publication_date>2026-06-26T22:52:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705240</loc>
  <lastmod>2026-06-26T22:01:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リカレント深層学習で脳画像を読む（Analyzing Neuroimaging Data Through Recurrent Deep Learning Models）</news:title>
   <news:publication_date>2026-06-26T22:01:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705238</loc>
  <lastmod>2026-06-26T22:01:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話行為を段階的に獲得するロボット学習（Stepwise Acquisition of Dialogue Act Through Human-Robot Interaction）</news:title>
   <news:publication_date>2026-06-26T22:01:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705236</loc>
  <lastmod>2026-06-26T22:00:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前処理選択とAutoMLパイプライン設計（Preprocessor Selection for Machine Learning Pipelines）</news:title>
   <news:publication_date>2026-06-26T22:00:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705234</loc>
  <lastmod>2026-06-26T22:00:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形時系列のクラスタリング：ベイズ非パラメトリックと粒子法の接合（Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach）</news:title>
   <news:publication_date>2026-06-26T22:00:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705232</loc>
  <lastmod>2026-06-26T22:00:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブランドはロゴだけでは語れない（Brand &amp;gt; Logo: Visual Analysis of Fashion Brands）</news:title>
   <news:publication_date>2026-06-26T22:00:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705230</loc>
  <lastmod>2026-06-26T21:59:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>方策勾配で学ぶ古典的プランニング戦略（Learning Classical Planning Strategies with Policy Gradient）</news:title>
   <news:publication_date>2026-06-26T21:59:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705228</loc>
  <lastmod>2026-06-26T21:59:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で加速するライクリー・フリーなイベント再構成（Machine Learning Accelerated Likelihood-Free Event Reconstruction in Dark Matter Direct Detection）</news:title>
   <news:publication_date>2026-06-26T21:59:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705226</loc>
  <lastmod>2026-06-26T21:08:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DIREによる動的尤度フリー推論（Dynamic Likelihood-free Inference via Ratio Estimation）</news:title>
   <news:publication_date>2026-06-26T21:08:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705224</loc>
  <lastmod>2026-06-26T21:07:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種大規模データの統合とバッチ補正（Heterogeneous large datasets integration using Bayesian factor regression）</news:title>
   <news:publication_date>2026-06-26T21:07:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705222</loc>
  <lastmod>2026-06-26T21:07:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙モデルのための効率的ベイズ実験設計（Efficient Bayesian Experimental Design for Implicit Models）</news:title>
   <news:publication_date>2026-06-26T21:07:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705220</loc>
  <lastmod>2026-06-26T21:07:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチクラウド環境における異常検知と攻撃分類の機械学習（Machine Learning for Anomaly Detection and Categorization in Multi-cloud Environments）</news:title>
   <news:publication_date>2026-06-26T21:07:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705218</loc>
  <lastmod>2026-06-26T21:06:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平面調和系の量子散逸：Maxwell–Chern–Simons理論（Quantum dissipation of planar harmonic systems: Maxwell-Chern-Simons theory）</news:title>
   <news:publication_date>2026-06-26T21:06:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705216</loc>
  <lastmod>2026-06-26T21:06:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウドセキュリティにおける教師あり機械学習の適用可能性（Feasibility of Supervised Machine Learning for Cloud Security）</news:title>
   <news:publication_date>2026-06-26T21:06:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705214</loc>
  <lastmod>2026-06-26T21:06:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Juliaプログラムと機械学習モデルの自動完全コンパイルをCloud TPUへ（Compiling Julia to TPUs）</news:title>
   <news:publication_date>2026-06-26T21:06:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705212</loc>
  <lastmod>2026-06-26T20:15:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語長を削減した深層ニューラルネットワーク推論（DEEP NEURAL NETWORK INFERENCE WITH REDUCED WORD LENGTH）</news:title>
   <news:publication_date>2026-06-26T20:15:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705210</loc>
  <lastmod>2026-06-26T20:14:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DropFilter: 畳み込み層のためのドロップアウト最適化（DropFilter: Dropout for Convolutions）</news:title>
   <news:publication_date>2026-06-26T20:14:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705208</loc>
  <lastmod>2026-06-26T20:14:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層依存型クロスプラットフォーム多視点特徴学習による施設カテゴリ推定（Hierarchy-Dependent Cross-Platform Multi-View Feature Learning for Venue Category Prediction）</news:title>
   <news:publication_date>2026-06-26T20:14:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705206</loc>
  <lastmod>2026-06-26T20:13:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一筆書きで注目領域を守る仕組み――Self-Erasing Networkによる弱教師ありオブジェクト注意の改善 (Self-Erasing Network for Integral Object Attention)</news:title>
   <news:publication_date>2026-06-26T20:13:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705204</loc>
  <lastmod>2026-06-26T20:13:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DCSVMによる高速多クラス分類（DCSVM: FAST MULTI-CLASS CLASSIFICATION USING SUPPORT VECTOR MACHINES）</news:title>
   <news:publication_date>2026-06-26T20:13:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705202</loc>
  <lastmod>2026-06-26T20:13:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANの訓練を安定化する混合ナッシュ均衡への接近（Finding Mixed Nash Equilibria of Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-26T20:13:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705200</loc>
  <lastmod>2026-06-26T20:12:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視点発見と理解のためのネットワーク手法（Viewpoint Discovery and Understanding in Social Networks）</news:title>
   <news:publication_date>2026-06-26T20:12:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705198</loc>
  <lastmod>2026-06-26T19:21:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確かな通信環境下での遠隔状態推定における最適スケジューリング学習（Learning Optimal Scheduling Policy for Remote State Estimation under Uncertain Channel Condition）</news:title>
   <news:publication_date>2026-06-26T19:21:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705196</loc>
  <lastmod>2026-06-26T19:21:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幼児語彙を用いた大規模照応解決データセット PreCo（PreCo: A Large-scale Dataset in Preschool Vocabulary for Coreference Resolution）</news:title>
   <news:publication_date>2026-06-26T19:21:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705194</loc>
  <lastmod>2026-06-26T19:20:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小売店向け果物・野菜識別に機械学習を使う試み（Fruit and Vegetable Identification Using Machine Learning for Retail Applications）</news:title>
   <news:publication_date>2026-06-26T19:20:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705192</loc>
  <lastmod>2026-06-26T19:19:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市交通における歩行者の行動・意図認識（Action and intention recognition of pedestrians in urban traffic）</news:title>
   <news:publication_date>2026-06-26T19:19:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705190</loc>
  <lastmod>2026-06-26T19:19:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M87のイオン化ガスフィラメントの特性（Properties of the ionised gas filament of M87）</news:title>
   <news:publication_date>2026-06-26T19:19:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705188</loc>
  <lastmod>2026-06-26T19:19:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SING: 軽量な波形生成で音を合成する新流儀（SING: Symbol-to-Instrument Neural Generator）</news:title>
   <news:publication_date>2026-06-26T19:19:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705186</loc>
  <lastmod>2026-06-26T19:19:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>算術的操作法からみるSobolev–Jacobi多項式（Operational Methods in the Study of Sobolev-Jacobi Polynomials）</news:title>
   <news:publication_date>2026-06-26T19:19:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705184</loc>
  <lastmod>2026-06-26T18:27:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォトメトリック赤方偏移の確率密度関数の統計解析（Statistical analysis of probability density functions for photometric redshifts through the KiDS-ESO-DR3 galaxies）</news:title>
   <news:publication_date>2026-06-26T18:27:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705182</loc>
  <lastmod>2026-06-26T18:27:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間とコーパスに敏感なエンティティ関連度の評価（Time-Aware and Corpus-Specific Entity Relatedness）</news:title>
   <news:publication_date>2026-06-26T18:27:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705180</loc>
  <lastmod>2026-06-26T18:27:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的意味再ランク付けによるテキストスポッティングの改善（Visual Semantic Re-ranker for Text Spotting）</news:title>
   <news:publication_date>2026-06-26T18:27:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705178</loc>
  <lastmod>2026-06-26T18:26:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LoGAN：色を条件にロゴを生成するAI（LoGAN: Generating Logos with a Generative Adversarial Neural Network Conditioned on color）</news:title>
   <news:publication_date>2026-06-26T18:26:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705176</loc>
  <lastmod>2026-06-26T18:26:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み付きスキップ接続による原子表現の解析（Analysis of Atomistic Representations Using Weighted Skip-Connections）</news:title>
   <news:publication_date>2026-06-26T18:26:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705174</loc>
  <lastmod>2026-06-26T18:26:18Z</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自然言語推論における汎化力の検証（Testing the Generalization Power of Neural Network Models Across NLI Benchmarks）</news:title>
   <news:publication_date>2026-06-26T18:26:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705172</loc>
  <lastmod>2026-06-26T18:25:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムフォレストのPAC-ベイズ境界に関する考察（On PAC-Bayesian Bounds for Random Forests）</news:title>
   <news:publication_date>2026-06-26T18:25:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705170</loc>
  <lastmod>2026-06-26T17:34:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OCAPIS：Scalaで構築されたR向け序数データ処理パッケージ（OCAPIS: R package for Ordinal Classification And Preprocessing In Scala）</news:title>
   <news:publication_date>2026-06-26T17:34:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705168</loc>
  <lastmod>2026-06-26T17:34:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチUAVによるサイバーフィジカルシステム設計の課題と展望（Multi-UAV Design Challenges for Cyber-Physical Systems）</news:title>
   <news:publication_date>2026-06-26T17:34:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705166</loc>
  <lastmod>2026-06-26T17:34:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>領域選択型コスト効率的アクティブラーニングによるセマンティックセグメンテーション（CEREALS: Cost-Effective REgion-based Active Learning for Semantic Segmentation）</news:title>
   <news:publication_date>2026-06-26T17:34:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705164</loc>
  <lastmod>2026-06-26T17:33:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適切な交通規制の自動発見（Finding Appropriate Traffic Regulations via Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-06-26T17:33:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705162</loc>
  <lastmod>2026-06-26T17:33:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cheeger変形による正のリッチ曲率の再考（Positive Ricci curvature through Cheeger deformations）</news:title>
   <news:publication_date>2026-06-26T17:33:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705160</loc>
  <lastmod>2026-06-26T17:33:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語からの構造対応プログラム合成（Structure-Aware Program Synthesis from Natural Language）</news:title>
   <news:publication_date>2026-06-26T17:33:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705158</loc>
  <lastmod>2026-06-26T17:32:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からのSVBRDF推定とレンダリング認識型深層ネットワーク（Single-Image SVBRDF Capture with a Rendering-Aware Deep Network）</news:title>
   <news:publication_date>2026-06-26T17:32:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705156</loc>
  <lastmod>2026-06-26T16:42:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一枚画像から光と色を分ける方法（Consistency-aware Shading Orders Selective Fusion for Intrinsic Image Decomposition）</news:title>
   <news:publication_date>2026-06-26T16:42:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705154</loc>
  <lastmod>2026-06-26T16:41:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習におけるセキュリティ問題と未解決の課題（The Faults in Our π∗s: Security Issues and Open Challenges in Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-26T16:41:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705152</loc>
  <lastmod>2026-06-26T16:41:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フリジア語─オランダ語の混合音声に対する半教師あり音響モデル訓練（Semi-supervised acoustic model training for speech with code-switching）</news:title>
   <news:publication_date>2026-06-26T16:41:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705150</loc>
  <lastmod>2026-06-26T16:40:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SwitchNetによる散乱問題の順逆写像学習（SWITCHNET: A NEURAL NETWORK MODEL FOR FORWARD AND INVERSE SCATTERING PROBLEMS）</news:title>
   <news:publication_date>2026-06-26T16:40:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705148</loc>
  <lastmod>2026-06-26T16:40:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二値関数の類似性を学習するグラフ埋め込み（Unsupervised Features Extraction for Binary Similarity Using Graph Embedding Neural Networks）</news:title>
   <news:publication_date>2026-06-26T16:40:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705146</loc>
  <lastmod>2026-06-26T16:39:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サーバーレスで学ぶ線形代数の実行基盤（numpywren: Serverless Linear Algebra）</news:title>
   <news:publication_date>2026-06-26T16:39:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705144</loc>
  <lastmod>2026-06-26T16:39:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分的フィードバックと切替コスト下のオンライン学習（Online learning with feedback graphs and switching costs）</news:title>
   <news:publication_date>2026-06-26T16:39:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705142</loc>
  <lastmod>2026-06-26T15:47:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>順序的な希薄3Dデータからの顔認識と深層登録（Face Recognition from Sequential Sparse 3D Data via Deep Registration）</news:title>
   <news:publication_date>2026-06-26T15:47:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705140</loc>
  <lastmod>2026-06-26T15:47:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ化された行動空間における階層的強化学習の提案（Hierarchical Approaches for Reinforcement Learning in Parameterized Action Space）</news:title>
   <news:publication_date>2026-06-26T15:47:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705138</loc>
  <lastmod>2026-06-26T15:47:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ナップサック付きバンディット問題の統一化（Unifying the stochastic and the adversarial Bandits with Knapsack）</news:title>
   <news:publication_date>2026-06-26T15:47:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705136</loc>
  <lastmod>2026-06-26T15:46:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像キャプションのニューラル合成パラダイム（A Neural Compositional Paradigm for Image Captioning）</news:title>
   <news:publication_date>2026-06-26T15:46:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705134</loc>
  <lastmod>2026-06-26T15:46:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トピック表現：トピックモデルでより代表的な単語を見つける（Topic representation: finding more representative words in topic models）</news:title>
   <news:publication_date>2026-06-26T15:46:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705132</loc>
  <lastmod>2026-06-26T15:45:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>冗長性が原因だった：敵対的事例を「1ビット」で理解する（ONE BIT MATTERS: UNDERSTANDING ADVERSARIAL EXAMPLES AS THE ABUSE OF REDUNDANCY）</news:title>
   <news:publication_date>2026-06-26T15:45:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705130</loc>
  <lastmod>2026-06-26T15:45:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群を用いた場所認識にCNNを応用する手法（Point-cloud-based Place Recognition using CNN）</news:title>
   <news:publication_date>2026-06-26T15:45:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
</urlset>