41 citations · 73 across the 11 of their papers we have counts for
5 papers · 1 filter
Tree-Planner: Efficient Close-loop Task Planning with Large Language Models
Mengkang Hu, Yao Mu, Xinmiao Yu +7
This paper studies close-loop task planning, which refers to the process of generating a sequence of skills (a plan) to accomplish a specific goal while adapting the plan based on…
ChiPFormer: Transferable Chip Placement via Offline Decision Transformer
Yao Lai, Jinxin Liu, Zhentao Tang +3
Placement is a critical step in modern chip design, aiming to determine the positions of circuit modules on the chip canvas. Recent works have shown that reinforcement learning (RL…
MetaDiffuser: Diffusion Model as Conditional Planner for Offline Meta-RL
Fei Ni, Jianye Hao, Yao Mu +4
Recently, diffusion model shines as a promising backbone for the sequence modeling paradigm in offline reinforcement learning(RL). However, these works mostly lack the generalizati…
EmbodiedGPT: Vision-Language Pre-Training via Embodied Chain of Thought
Yao Mu, Qinglong Zhang, Mengkang Hu +7
Embodied AI is a crucial frontier in robotics, capable of planning and executing action sequences for robots to accomplish long-horizon tasks in physical environments. In this work…
Learnable Behavior Control: Breaking Atari Human World Records via Sample-Efficient Behavior Selection
Jiajun Fan, Yuzheng Zhuang, Yuecheng Liu +5
The exploration problem is one of the main challenges in deep reinforcement learning (RL). Recent promising works tried to handle the problem with population-based methods, which c…