LeanTutor: Towards a Verified AI Mathematical Proof Tutor
Manooshree Patel, Rayna Bhattacharyya, Thomas Lu, Arnav Mehta, Niels Voss, Narges Norouzi, Gireeja Ranade
Abstract
This paper considers the development of an AI-based provably-correct mathematical proof tutor. While Large Language Models (LLMs) allow seamless communication in natural language, they are error prone. Theorem provers such as Lean allow for provable-correctness, but these are hard for students to learn. We present a proof-of-concept system (LeanTutor) by combining the complementary strengths of LLMs and theorem provers. LeanTutor is composed of three modules: (i) an autoformalizer/proof-checker, (ii) a next-step generator, and (iii) a natural language feedback generator. To evaluate the system, we introduce PeanoBench, a dataset of 371 Peano Arithmetic proofs in human-written natural language and formal language, derived from the Natural Numbers Game.
BibTeX
@inproceedings{aaai2026_leantutortowards,
title = {LeanTutor: Towards a Verified AI Mathematical Proof Tutor},
author = {Manooshree Patel and Rayna Bhattacharyya and Thomas Lu and Arnav Mehta and Niels Voss and Narges Norouzi and Gireeja Ranade},
booktitle = {AAAI 2026},
year = {2026}
}