A new analysis challenges the assumption that constrained decoding inherently degrades Large Language Model reasoning, examining the claim through a taxonomy of three constraint types, beginning with format constraints that enforce output structure. The work revisits how constrained decoding, which guarantees LLM outputs conform to predefined formats, affects model performance.
Constrained decoding guarantees that Large Language Models (LLMs) produce outputs conforming to predefined formats, but is often assumed to inherently degrade reasoning. We examine this assumption through a taxonomy of three constraint types: format constraints, which enforce output structure; valid
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