ProgCo: Program Helps Self-Correction of Large Language Models
Authors: name: Xiaoshuai Song, name: Yanan Wu, name: Weixun Wang, name: Jiaheng Liu, name: Wenbo Su, name: Bo Zheng

Self-Correction aims to enable large language models (LLMs) to self-verify
and self-refine their initial responses without external feedback. However,
LLMs often fail to effectively self-verify and generate correct feedback,
further misleading refinement and leading to the failure of self-correction,
especially in complex reasoning tasks. In this paper, we propose Program-driven
Self-Correction (ProgCo). First, program-driven verification (ProgVe) achieves
complex verification logic and extensive validation through self-generated,
self-executing verification pseudo-programs. Then, program-driven refinement
(ProgRe) receives feedback from ProgVe, conducts dual reflection and refinement
on both responses and verification programs to mitigate misleading of incorrect
feedback in complex reasoning tasks. Experiments on three instruction-following
and mathematical benchmarks indicate that ProgCo achieves effective
self-correction, and can be further enhance performance when combined with real
program tools.