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Dyve: Thinking Fast and Slow for Dynamic Process Verification (2502.11157v1)

Published 16 Feb 2025 in cs.AI

Abstract: We present Dyve, a dynamic process verifier that enhances reasoning error detection in LLMs 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.

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