10 citations · 11 across the 6 of their papers we have counts for
6 papers
-mem: Efficient Online Memory for Large Language Models
Jingdi Lei, Di Zhang, Junxian Li +7
Large language models increasingly need to accumulate and reuse historical information in long-term assistants and agent systems. Simply expanding the context window is costly and…
Integrating Diffusion-based Multi-task Learning with Online Reinforcement Learning for Robust Quadruped Robot Control
Xinyao Qin, Xiaoteng Ma, Yang Qi +6
Recent research has highlighted the powerful capabilities of imitation learning in robotics. Leveraging generative models, particularly diffusion models, these approaches offer not…
Episodic Novelty Through Temporal Distance
Yuhua Jiang, Qihan Liu, Yiqin Yang +8
Exploration in sparse reward environments remains a significant challenge in reinforcement learning, particularly in Contextual Markov Decision Processes (CMDPs), where environment…
Efficient Multi-agent Reinforcement Learning by Planning
Qihan Liu, Jianing Ye, Xiaoteng Ma +3
Multi-agent reinforcement learning (MARL) algorithms have accomplished remarkable breakthroughs in solving large-scale decision-making tasks. Nonetheless, most existing MARL algori…
Learning Diverse Risk Preferences in Population-based Self-play
Yuhua Jiang, Qihan Liu, Xiaoteng Ma +5
Among the great successes of Reinforcement Learning (RL), self-play algorithms play an essential role in solving competitive games. Current self-play algorithms optimize the agent…
Offline Reinforcement Learning with Value-based Episodic Memory
Xiaoteng Ma, Yiqin Yang, Hao Hu +5
Offline reinforcement learning (RL) shows promise of applying RL to real-world problems by effectively utilizing previously collected data. Most existing offline RL algorithms use…