AI RESEARCH
What is Holding Back Latent Visual Reasoning?
arXiv CS.LG
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ArXi:2605.18445v1 Announce Type: cross Humans can approach complex visual problems by mentally simulating intermediate visual steps, rather than reasoning through language alone. Inspired by this, several works on Vision-Language Models have recently explored chain-of-thought reasoning with continuous latent tokens as intermediate visual imagination steps. In this work, we investigate how recent models leverage such latent tokens. Surprisingly, we find that model accuracy is unaffected when latent tokens are replaced by uninformative ``dummy'' tokens.