5 citations · 17 across the 14 of their papers we have counts for
6 papers · 1 filter
Videos are Sample-Efficient Supervisions: Behavior Cloning from Videos via Latent Representations
Xin Liu, Haoran Li, Dongbin Zhao
Humans can efficiently extract knowledge and learn skills from the videos within only a few trials and errors. However, it poses a big challenge to replicate this learning process…
Generalizing Consistency Policy to Visual RL with Prioritized Proximal Experience Regularization
Haoran Li, Zhennan Jiang, Yuhui Chen +1
With high-dimensional state spaces, visual reinforcement learning (RL) faces significant challenges in exploitation and exploration, resulting in low sample efficiency and training…
SELU: Self-Learning Embodied MLLMs in Unknown Environments
Boyu Li, Haobin Jiang, Ziluo Ding +4
Recently, multimodal large language models (MLLMs) have demonstrated strong visual understanding and decision-making capabilities, enabling the exploration of autonomously improvin…
Learning Future Representation with Synthetic Observations for Sample-efficient Reinforcement Learning
Xin Liu, Yaran Chen, Dongbin Zhao
In visual Reinforcement Learning (RL), upstream representation learning largely determines the effect of downstream policy learning. Employing auxiliary tasks allows the agent to e…
Boosting Continuous Control with Consistency Policy
Yuhui Chen, Haoran Li, Dongbin Zhao
Due to its training stability and strong expression, the diffusion model has attracted considerable attention in offline reinforcement learning. However, several challenges have al…
Cross-domain Random Pre-training with Prototypes for Reinforcement Learning
Xin Liu, Yaran Chen, Haoran Li +2
This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible. Unsupervised c…