English

LeanGeo: Formalizing Competitional Geometry problems in Lean

Artificial Intelligence 2025-08-21 v1

Abstract

Geometry problems are a crucial testbed for AI reasoning capabilities. Most existing geometry solving systems cannot express problems within a unified framework, thus are difficult to integrate with other mathematical fields. Besides, since most geometric proofs rely on intuitive diagrams, verifying geometry problems is particularly challenging. To address these gaps, we introduce LeanGeo, a unified formal system for formalizing and solving competition-level geometry problems within the Lean 4 theorem prover. LeanGeo features a comprehensive library of high-level geometric theorems with Lean's foundational logic, enabling rigorous proof verification and seamless integration with Mathlib. We also present LeanGeo-Bench, a formal geometry benchmark in LeanGeo, comprising problems from the International Mathematical Olympiad (IMO) and other advanced sources. Our evaluation demonstrates the capabilities and limitations of state-of-the-art Large Language Models on this benchmark, highlighting the need for further advancements in automated geometric reasoning. We open source the theorem library and the benchmark of LeanGeo at https://github.com/project-numina/LeanGeo/tree/master.

Keywords

Cite

@article{arxiv.2508.14644,
  title  = {LeanGeo: Formalizing Competitional Geometry problems in Lean},
  author = {Chendong Song and Zihan Wang and Frederick Pu and Haiming Wang and Xiaohan Lin and Junqi Liu and Jia Li and Zhengying Liu},
  journal= {arXiv preprint arXiv:2508.14644},
  year   = {2025}
}

Comments

28 pages

R2 v1 2026-07-01T04:58:22.797Z