1 citations · 1 across the 5 of their papers we have counts for
5 papers
FineMoLA: Towards Fine-Grained Motion-Language Alignment from Clip-Level Supervision
Tongyan Wang, Zhengyuan Li, Muhan Lin +5
Text-conditioned human motion generation has made rapid progress with the emergence of large-scale motion--language datasets. However, even datasets with rich long-form description…
MAPL: Multi-Objective Preference Learning for Robot Locomotion
Xiyue Chen, Muhan Lin, Shuyang Shi +1
Reward design remains a major bottleneck in reinforcement learning for robot locomotion, where successful policies often depend on carefully tuned, task-specific reward functions.…
Speaking the Language of Teamwork: LLM-Guided Credit Assignment in Multi-Agent Reinforcement Learning
Muhan Lin, Shuyang Shi, Yue Guo +7
Credit assignment, the process of attributing credit or blame to individual agents for their contributions to a team's success or failure, remains a fundamental challenge in multi-…
Speedup Techniques for Switchable Temporal Plan Graph Optimization
He Jiang, Muhan Lin, Jiaoyang Li
Multi-Agent Path Finding (MAPF) focuses on planning collision-free paths for multiple agents. However, during the execution of a MAPF plan, agents may encounter unexpected delays,…
Navigating Noisy Feedback: Enhancing Reinforcement Learning with Error-Prone Language Models
Muhan Lin, Shuyang Shi, Yue Guo +6
The correct specification of reward models is a well-known challenge in reinforcement learning. Hand-crafted reward functions often lead to inefficient or suboptimal policies and m…