8 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.LG2025
Generative Actor Critic
Aoyang Qin, Deqian Kong, Wei Wang +3
Conventional Reinforcement Learning (RL) algorithms, typically focused on estimating or maximizing expected returns, face challenges when refining offline pretrained models with on…
cs.RO2024
InterPreT: Interactive Predicate Learning from Language Feedback for Generalizable Task Planning
Muzhi Han, Yifeng Zhu, Song-Chun Zhu +2
Learning abstract state representations and knowledge is crucial for long-horizon robot planning. We present InterPreT, an LLM-powered framework for robots to learn symbolic predic…
cs.RO2024★ 8 cited
LLM3:Large Language Model-based Task and Motion Planning with Motion Failure Reasoning
Shu Wang, Muzhi Han, Ziyuan Jiao +4
Conventional Task and Motion Planning (TAMP) approaches rely on manually crafted interfaces connecting symbolic task planning with continuous motion generation. These domain-specif…