5 papers
Omni-Sleep: A Sleep Foundation Model via Hierarchical Contrastive Learning of CNS-ANS Dynamics
Zhoujie Hou, Song Wang, Kexin Lou +3
Sleep physiology arises from the coordinated dynamics of the central nervous system (CNS) and autonomic nervous system (ANS), as reflected by multimodal polysomnography signals inc…
OmniEEG-Bench: A Standardized Evaluation Benchmark for EEG Foundation Models
Ziling Lu, Zongsheng Li, Xinke Shen +11
Electroencephalography (EEG) supports a variety of brain-computer interface (BCI) tasks ranging from brain-state monitoring to human-LLM interactions. EEG foundation models are eme…
Behavior-Invariant Task Representation Learning with Transformer-based World Models for Offline Meta-Reinforcement Learning
Fuyuan Qian, Menglong Zhang, Song Wang +1
Offline meta-reinforcement learning leverages static datasets to enable agents to generalize to unseen environments by combining offline efficiency with meta-learning adaptability,…
Learning Task Belief Similarity with Latent Dynamics for Meta-Reinforcement Learning
Menglong Zhang, Fuyuan Qian
Meta-reinforcement learning requires utilizing prior task distribution information obtained during exploration to rapidly adapt to unknown tasks. The efficiency of an agent's explo…
Memory Sequence Length of Data Sampling Impacts the Adaptation of Meta-Reinforcement Learning Agents
Menglong Zhang, Fuyuan Qian, Quanying Liu
Fast adaptation to new tasks is extremely important for embodied agents in the real world. Meta-reinforcement learning (meta-RL) has emerged as an effective method to enable fast a…