8 citations · 10 across the 8 of their papers we have counts for
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cs.AI2024
Robot Policy Learning with Temporal Optimal Transport Reward
Yuwei Fu, Haichao Zhang, Di Wu +2
Reward specification is one of the most tricky problems in Reinforcement Learning, which usually requires tedious hand engineering in practice. One promising approach to tackle thi…
cs.RO2024★ 1 cited
Solving Motion Planning Tasks with a Scalable Generative Model
Yihan Hu, Siqi Chai, Zhening Yang +6
As autonomous driving systems being deployed to millions of vehicles, there is a pressing need of improving the system's scalability, safety and reducing the engineering cost. A re…
cs.LG2024★ 1 cited
FuRL: Visual-Language Models as Fuzzy Rewards for Reinforcement Learning
Yuwei Fu, Haichao Zhang, Di Wu +2
In this work, we investigate how to leverage pre-trained visual-language models (VLM) for online Reinforcement Learning (RL). In particular, we focus on sparse reward tasks with pr…