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MLEIL 2026: International Conference on Machine Learning, Embodied Intelligence and Large Models

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MLEIL
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投稿締切日:
2026-09-03 Extended
通知日:
2026-10-05
開催日:
2026-10-23
開催地:
Changsha, China
閲覧: 1176   フォロー: 0   参加: 0

会伴インデックス (CP-I)

45.0 / 100
全 5,651 件中 第 2,746 位 · 上位 49%

人工知能・機械学習 分野 736 件中 第 298 位

根拠が限られています：この会議は CCF / ICORE / QUALIS のいずれにも収録されておらず、採択率のデータもないため、スコアの大部分は中立の基準値に戻ります。
学術的評価 (35%) データなし — 中立の基準値 50 点として算入 —
投稿の選択性 (20%) データなし — 中立の基準値 50 点として算入 —
開催回数 (20%) データなし — 中立の基準値 50 点として算入 —
コミュニティの注目度 (10%)
23
公開情報の充実度 (15%)
35

使用した入力: 過去 24 か月にこのページを開いた研究者：20 人

公開情報で不足しているもの: 過去の採択率 (+4.5) · 過去の開催回 (+3.0) · 最優秀論文の記録 (+2.3)
主催者は会議を認証申請したうえで、このページから直接追加できます。スコアは毎晩再計算されます。このスコアを上げるには

信頼度 25% — スコアのうち、中立の基準値ではなく実際に観測されたデータに基づく割合。 このスコアの算出方法 · ランキングを見る · アルゴリズム版 1.1 · 算出日 2026-09-07

論文募集

MLEIL 2026 (International Conference on Machine Learning, Embodied Intelligence and Large Models) is an academic conference held in Changsha, China on 2026-10-23. The paper submission deadline is 2026-09-03 (extended). Acceptance notifications are sent on 2026-10-05.

The International Conference on Machine Learning, Embodied Intelligence and Large Models (MLEIL) is dedicated to focusing on cutting-edge interdisciplinary research within the field of artificial intelligence, establishing a high-calibre academic exchange platform for researchers worldwide. Centred on machine learning theory, embodied intelligent systems, and large-scale model technologies, the conference brings together domestic and international experts to share cutting-edge research findings and innovative advancements while exploring critical scientific questions and technical challenges. Through in-depth exchanges and intellectual discourse, it propels the profound integration and innovative development of large-scale models, multimodal learning, autonomous agents, and robotic systems. This fosters collaborative innovation across industry, academia, and research, thereby accelerating breakthroughs in artificial intelligence technologies and facilitating their high-quality practical implementation. Machine Learning Architecture Design for Robotic Foundation Models Embodied Agents Theoretical Foundations of Embodied Intelligence Reinforcement Learning and Imitation Learning from Multimodal Data Continual/Lifelong Learning Embodied Intelligent Agent Perception and Motion Planning Embodied Driving Agents Multimodal Embodied Learning and Decision-making Tactile Feedback and Multisensory Fusion Interaction Embodied Interaction in Human-computer Collaboration Visual Language Action Multimodal Alignment Collaborative Interaction between Swarm Intelligence and Multi-agent Systems Cognitive Reasoning and Scene Understanding Application of Embodied Systems in Healthcare and Industry General Machine Learning Deep Learning Theory of Machine Learning Machine Learning Systems Optimisation Probabilistic Methods Reinforcement Learning Trustworthy Machine Learning Application-driven Machine Learning Health, Bioinformatics Industrial and Engineering Applications Security Applications Smart Cities and Autonomous Driving Intelligent Virtual Environments Embodied Intelligence Architecture Design for Robotic Foundation Models Embodied Agents Theoretical Foundations of Embodied Intelligence Reinforcement Learning and Imitation Learning from Multimodal Data Continual/Lifelong Learning Embodied Intelligent Agent Perception and Motion Planning Embodied Driving Agents Multimodal Embodied Learning and Decision-making Tactile Feedback and Multisensory Fusion Interaction Embodied Interaction in Human-computer Collaboration Visual Language Action Multimodal Alignment Collaborative Interaction between Swarm Intelligence and Multi-agent Systems Cognitive Reasoning and Scene Understanding Application of Embodied Systems in Healthcare and Industry Large Model Generative Large-scale Models Large-scale Models Integrating Visual and Optical Sensing Multimodal Fusion Training and Optimization of Large-scale Models Large-scale Distributed Training Hardware Acceleration and Heterogeneous Computing Visual Large-scale Models Clinical Decision Support Agents Generative Medical Imaging Industrial Autonomous Agents Driving Foundation Models Autonomous Inspection Systems Intelligent Video Surveillance Cybersecurity and Autonomous Intelligence
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