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REAL-Prover: Retrieval Augmented Lean Prover for Mathematical Reasoning

27 May 2025
Ziju Shen
Naohao Huang
Fanyi Yang
Yutong Wang
Guoxiong Gao
Tianyi Xu
Jiedong Jiang
Wanyi He
Pu Yang
Mengzhou Sun
Haocheng Ju
Peihao Wu
Bryan Dai
B. Dong
    AIMatLRM
ArXiv (abs)PDFHTML
Main:9 Pages
5 Figures
Bibliography:3 Pages
6 Tables
Appendix:3 Pages
Abstract

Nowadays, formal theorem provers have made monumental progress on high-school and competition-level mathematics, but few of them generalize to more advanced mathematics. In this paper, we present REAL-Prover, a new open-source stepwise theorem prover for Lean 4 to push this boundary. This prover, based on our fine-tuned large language model (REAL-Prover-v1) and integrated with a retrieval system (Leansearch-PS), notably boosts performance on solving college-level mathematics problems. To train REAL-Prover-v1, we developed HERALD-AF, a data extraction pipeline that converts natural language math problems into formal statements, and a new open-source Lean 4 interactive environment (Jixia-interactive) to facilitate synthesis data collection. In our experiments, our prover using only supervised fine-tune achieves competitive results with a 23.7% success rate (Pass@64) on the ProofNet dataset-comparable to state-of-the-art (SOTA) models. To further evaluate our approach, we introduce FATE-M, a new benchmark focused on algebraic problems, where our prover achieves a SOTA success rate of 56.7% (Pass@64).

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