Dyve: Thinking Fast and Slow for Dynamic Process Verification
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.
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Jianyuan Zhong
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2025-02-18T09:30:45.385Z
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Zhong
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Jianyuan1
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Zeju Li
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2025-02-18T16:39:43.674Z
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Zeju Li
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zeju-0727
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Zhijian Xu
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2025-06-18T12:18:01.021Z
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zhijianxu
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VEWOXIC
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Xiangyu Wen
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2025-02-18T16:39:45.646Z
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Xiangyu Wen
user
XiangyuWen
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Qiang Xu
Dyve: Thinking Fast and Slow for Dynamic Process Verification
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.
Dyve, a dynamic process verifier, enhances error detection in large language models by integrating fast and slow thinking processes and leveraging a consensus-filtered process supervision technique with Monte Carlo estimation.
dynamic process verifier fast thinking slow thinking Systems Theory token-level confirmation comprehensive analysis step-wise consensus-filtered Monte Carlo estimation process-based verifiers Best-of-N settings