Preprint
Aug 2026
Enhancing VLM Reward Models Through Structure-Aware Fine-Tuning
Designing effective reward functions remains a major bottleneck in Reinforcement Learning (RL). Recent work uses large foundation Vision-Language Models (VLMs) as reward models, computing text-observation similarity to bypass manual reward engineering. Although promising, these rewards are often noisy and unreliable, l...
Pyrros Koussios, Chen-Hao Li, Xin Chen et al.
· 0 citations