Seed-Prover: Deep and Broad Reasoning for Automated Theorem Proving
Luoxin Chen, Jinming Gu, Liankai Huang, Wenhao Huang, Zhicheng Jiang, Allan Jie, Xiaoran Jin, Xing Jin, Chenggang Li, Kaijing Ma, Cheng Ren, Jiawei Shen, Wenlei Shi, Tong Sun, He Sun, Jiahui Wang, Siran Wang, Zhihong Wang, Chenrui Wei, Shufa Wei, Yonghui Wu, Yuchen Wu
2025-08-01
Summary
This paper talks about Seed-Prover, a new AI system that helps automatically prove complex math theorems by breaking down problems into smaller steps and improving proofs iteratively with feedback.
What's the problem?
The problem is that automated theorem proving is very challenging because math proofs are complex and require deep and broad reasoning, which most AI models struggle with, especially without clear guidance on correctness.
What's the solution?
Seed-Prover uses a method that mimics how human mathematicians work by first proving useful smaller results called lemmas. It refines its proofs step-by-step using feedback from a formal verification system called Lean. It also includes a special tool for solving geometry problems efficiently. This approach allows the system to handle difficult math problems, including those from the International Mathematical Olympiad.
Why it matters?
This matters because it shows AI can now assist in solving very challenging math problems automatically, which can help mathematicians, educators, and students by speeding up research and making complex reasoning more accessible.
Abstract
Seed-Prover, a lemma-style reasoning model using Lean, achieves high performance in formal theorem proving and automated mathematical reasoning through iterative refinement and specialized geometry support.