Knowing When to Quit: A Principled Framework for Dynamic Abstention in LLM Reasoning

arXiv:2604.18419v4 Announce Type: replace-cross Abstract: LLMs utilizing chain-of-thought reasoning often waste substantial compute by producing long, incorrect responses. Abstention can mitigate this by withholding outputs unlikely to be correct. While most abstention methods decide to withhold outputs before or after generation, dynamic mid-generation abstention considers early termination of unpromising reasoning traces at each token position. Prior work has explored empirical variants of this idea, but principled guidance for the abstention rule remains lacking. We present a formal analysi

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