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Proposes CART, a neuro-symbolic framework that interleaves natural language reasoning steps with symbolic constraint assertions to detect and correct errors early in chain-of-thought traces for multimodal LLMs. Reduces snowball rate from 65% to 14% and improves accuracy on multiple benchmarks.