Large Reward Models: Generalizable Online Robot Reward Generation with Vision-Language Models
The paper addresses difficulty in designing good reward functions for training robots using Reinforcement Learning. It proposes Large Reward Models (LRMs) that adapt vision-language models to create online reward generators. These LRMs produce a complex, multi-faceted reward signal based on visual observations, improving policy refinement through process, progress, and completion feedback.