Dyve: Thinking Fast and Slow for Dynamic Process Verification
Authors: name: Jianyuan Zhong; name: Zeju Li; name: Zhijian Xu; name: Xiangyu Wen; name: Qiang Xu
Published: 2025-02-16 15:11:19

Abstract: We present Dyve, a dynamic process verifier that enhances reasoning error
detection in large language models by integrating fast and slow thinking,
inspired by Kahneman's Systems Theory. Dyve adaptively applies immediate
token-level confirmation System 1 for straightforward steps and comprehensive
analysis System 2 for complex ones. Leveraging a novel step-wise
consensus-filtered process supervision technique, combining Monte Carlo
estimation with LLM based evaluation, Dyve curates high-quality supervision
signals from noisy data. Experimental results on ProcessBench and the MATH
dataset confirm that Dyve significantly outperforms existing process-based
verifiers and boosts performance in Best-of-N settings.