MLEIL 2026 (International Conference on Machine Learning, Embodied Intelligence and Large Models) is an academic conference held in Changsha, China on 2026-09-18. The paper submission deadline is 2026-07-28. Acceptance notifications are sent on 2026-09-02.
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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