Researchers extended Reinforcement Learning with Verifiable Rewards to Large Vision-Language Models and found that visual claims are not always supported by images. They introduced a diagnostic to measure the persistence of visual claims and proposed Persistence-Aware Credit Gating to attenuate credit for persistent claims.