MARVL: Multi-Stage Guidance for Robotic Manipulation via Vision-Language Models
arXiv:2602.15872v3 Announce Type: replace
Abstract: Designing dense reward functions is pivotal for efficient robotic Reinforcement Learning (RL). However, most dense rewards rely on manual engineering, which fundamentally limits the scalability and a…