5 citations · 17 across the 14 of their papers we have counts for
5 papers · 1 filter
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…
Advancing Object Goal Navigation Through LLM-enhanced Object Affinities Transfer
Mengying Lin, Shugao Liu, Dingxi Zhang +4
Object-goal navigation requires mobile robots to efficiently locate targets with visual and spatial information, yet existing methods struggle with generalization in unseen environ…
FM3Q: Factorized Multi-Agent MiniMax Q-Learning for Two-Team Zero-Sum Markov Game
Guangzheng Hu, Yuanheng Zhu, Haoran Li +1
Many real-world applications involve some agents that fall into two teams, with payoffs that are equal within the same team but of opposite sign across the opponent team. The so-ca…