CoRe: Combined Rewards with Vision-Language Model Feedback for Preference-Aligned Reinforcement Learning

arXiv:2607.01721v1 Announce Type: new Abstract: Reward design remains a central challenge in reinforcement learning (RL). Hand-crafted rewards are often difficult to specify and may lead to suboptimal policies, while learned rewards from preferences can suffer from inefficiency and unstable trainin