Study exposes brittleness in RL-finetuned vision language models under text perturbations.

Researchers show RL-finetuned VLMs remain vulnerable to weak visual grounding and text perturbations, with misleading captions or incorrect chain-of-thought traces causing substantial drops in robustness and confidence.