会议信息

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

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MLEIL
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截稿日期:
2026-09-03 Extended
通知日期:
2026-10-05
会议日期:
2026-10-23
会议地点:
Changsha, China
浏览: 1177   关注: 0   参加: 0

会伴指数 (CP-I)

45.0 / 100
全站第 2,746 名 / 共 5,651 个会议 · 前 49%

人工智能与机器学习 第 298 / 736

证据有限：这个会议不在 CCF / ICORE / QUALIS 任何一份榜单里，也没有录用率数据，因此分数的大部分回落到了中性基准。
学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%) 无数据 —— 按中性基准 50 分计入 —
社区关注 (10%)
23
资料公开度 (15%)
35

用到的输入: 过去 24 个月打开过本页的研究者：20 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0) · 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 25% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-09-07

征稿

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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