OPEN SOURCE

AutoformBench: A Lean Formalization Benchmark for Advanced Mathematics

October 13, 2026

Abstract

AI systems are increasingly capable of producing machine-checked Lean proofs of advanced mathematical results. Real mathematical formalization, however, is not isolated theorem proving: it requires building the definitions and intermediate lemmas that connect a result to a formal library. Existing evaluations often provide isolated theorem statements in settings where much of this supporting theory is already available in Mathlib. We introduce AutoformBench, a benchmark of 341 Lean 4 formalization tasks drawn from 24 advanced mathematical sources. Lean-experienced mathematicians formalized and audited each target statement, leaving the corresponding Lean proof to the evaluated agent. Each problem is embedded in a broader mathematical development: agents receive the informal proof but must translate it into Lean while constructing the missing definitions, intermediate lemmas, and supporting infrastructure. We compare the performance of frontier models on these problems. We find a largely shared difficulty frontier: success depends less on mathematical domain than on models' ability to construct missing formal infrastructure. Data and code at https://github.com/facebookresearch/autoformbench.

Download the Paper

AUTHORS

Written by

Charles Arnal

Ahmad Rammal

Niket Patel

Fabian Gloeckle

Bartosz Piotrowski

Amaury Hayat

Julia Kempe

Remi Munos

Vivien Cabannes

Publisher

arXiv

Related Publications

July 13, 2026

AR/VR

RESEARCH

S-EMBER: A Large-Scale Benchmark for Streaming Egocentric Memory Retrieval

Xiaodong Wang, Xuanyi Zhao, Pedro Rodriguez, Devendra Singh Sachan, Barlas Oguz, Seungwhan Moon, Shang-Wen Li, Gargi Ghosh, Xin Dong, Wen-Tau Yih

July 13, 2026

June 05, 2026

CONVERSATIONAL AI

RANKING AND RECOMMENDATIONS

Superintelligent Retrieval Agent: The Next Frontier of Agentic Retrieval

Zeyu Yang, Qi Ma, Jason Chen, Anshumali Shrivastava

June 05, 2026

May 27, 2026

OPEN SOURCE

AutoformBot: Formalizing Mathematics at Scale

Ahmad Rammal, Niket Patel, Amaury Hayat, Julia Kempe, Remi Munos, Charles Arnal, Vivien Cabannes

May 27, 2026

May 12, 2026

HUMAN & MACHINE INTELLIGENCE

RESEARCH

NeuralSet: A High-Performing Python Package for Neuro-AI

Jean Remi King, Corentin Bel, Linnea Evanson, Julien Gadonneix, Sophia Houhamdi, Jarod Levy, Josephine Raugel, Andrea Santos Revilla, Mingfang (Lucy) Zhang, Julie Bonnaire, Charlotte Caucheteux, Alexandre Défossez, Théo Desbordes, Pablo Diego-Simón, Shubh Khanna, Juliette Millet, Pierre Orhan, Saarang Panchavati, Antoine Ratouchniak, Alexis Thual, Teon Brooks, Katelyn Begany, Yohann Benchetrit, Marlene Careil, Hubert Jacob Banville, Stéphane d'Ascoli, Simon Dahan, Jérémy Rapin

May 12, 2026

Help Us Pioneer The Future of AI

We share our open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.