ATLAS is a Lean 4 library of textbook mathematics autoformalized by LLMs: informal statements and proofs translated into Lean code. It draws from undergraduate and graduate textbooks across analysis, algebra, geometry, topology, combinatorics, probability, statistics, PDEs, number theory, and theoretical computer science.
The goal of ATLAS is to provide reusable formal building blocks for future human- and machine-driven Lean formalization. This is an active effort: we are continuing to scale to more sources, curate the generated material, improve coverage and maintainability, and move the library closer to Mathlib conventions.
ATLAS was generated with AutoformBot, our autoformalization pipeline.
Each book directory under Atlas/ contains:
- Lean source files for the generated definitions, statements, and proofs.
targets.yaml, listing the textbook statements selected for formalization.report.json, containing automated evaluation results for matched Lean declarations, including faithfulness, proof-integrity, and code-quality scores.
A visualizer is provided at https://rammalahmad.github.io/atlas/. It allows users to browse ATLAS, compare informal statements with their Lean formalizations, inspect logical dependency graphs between results, and extract the Lean code needed to state a selected theorem.
ATLAS is an ongoing, machine-generated extension effort rather than a finished product. We are actively working on scaling the corpus, curating the generated code, formalizing remaining statements, and improving idiomatic Mathlib reuse. External contributions are welcome!
To build the full library with the pinned Lean and Mathlib versions, run:
26 books · 630,999 lines of code · 483,917 lines of Lean code (excl. comments/blanks) · 46,203 declarations · 42,837 proved (92.7%) · 2,855 / 4,007 statements formalized (71.3%) · 183,157M tokens
| Book | Target Statements | Formalized | % Formalized | Lines of Code | Lines of Lean | Declarations | Proved | % Proved | Tokens (M) |
|---|---|---|---|---|---|---|---|---|---|
| AlgebraNotes | 176 | 151 | 85.8% | 5,037 | 4,409 | 274 | 261 | 95.3% | 1,962.99 |
| AlgebraicCombinatorics | 39 | 37 | 94.9% | 10,695 | 9,343 | 737 | 734 | 99.6% | 1,440.73 |
| AlgebraicGeometryI | 186 | 112 | 60.2% | 40,678 | 27,393 | 4,499 | 4,210 | 93.6% | 7,629.26 |
| AlgebraicTopologyI | 171 | 110 | 64.3% | 29,154 | 20,142 | 2,416 | 2,063 | 85.4% | 10,323.27 |
| AnAlgorithmistsToolkit | 158 | 131 | 82.9% | 9,656 | 8,234 | 712 | 668 | 93.8% | 2,004.00 |
| ArithmeticGeometry | 335 | 266 | 79.4% | 39,257 | 29,573 | 3,047 | 2,861 | 93.9% | 11,100.62 |
| BooleanFunctions | 108 | 44 | 40.7% | 9,516 | 7,949 | 667 | 614 | 92.1% | 2,327.49 |
| Buildings | 74 | 44 | 59.5% | 64,383 | 48,809 | 4,345 | 4,247 | 97.7% | 20,442.93 |
| CombinatorialOptimization | 36 | 22 | 61.1% | 8,908 | 7,934 | 428 | 414 | 96.7% | 2,475.65 |
| ComplexVariables | 38 | 37 | 97.4% | 7,231 | 6,225 | 285 | 280 | 98.2% | 1,250.91 |
| DifferentialAnalysis | 113 | 88 | 77.9% | 31,302 | 23,713 | 1,634 | 1,506 | 92.2% | 11,743.27 |
| DifferentialGeometry | 147 | 112 | 76.2% | 10,592 | 8,942 | 888 | 781 | 88.0% | 1,933.97 |
| EllipticCurves | 360 | 212 | 58.9% | 32,819 | 22,316 | 3,483 | 2,981 | 85.6% | 11,058.00 |
| FourierAnalysis | 38 | 34 | 89.5% | 7,943 | 6,671 | 373 | 359 | 96.2% | 1,185.90 |
| GeometryOfManifolds | 72 | 40 | 55.6% | 22,686 | 16,408 | 3,251 | 3,098 | 95.3% | 6,864.93 |
| HighDimensionalStatistics | 73 | 65 | 89.0% | 39,656 | 31,715 | 1,564 | 1,518 | 97.1% | 975.36 |
| IntroductionToFunctionalAnalysis | 72 | 68 | 94.4% | 2,709 | 2,006 | 113 | 109 | 96.5% | 553.64 |
| IntroductionToPartialDifferentialEquations | 105 | 86 | 81.9% | 27,666 | 20,740 | 1,585 | 1,414 | 89.2% | 2,972.23 |
| LieGroups | 185 | 74 | 40.0% | 60,285 | 50,594 | 4,219 | 3,814 | 90.4% | 45,384.33 |
| NumberTheoryI | 576 | 460 | 79.9% | 64,958 | 54,760 | 3,764 | 3,591 | 95.4% | 15,424.36 |
| ProbabilisticMethodsInCombinatorics | 210 | 109 | 51.9% | 20,555 | 15,604 | 1,272 | 1,089 | 85.6% | 2,720.15 |
| ProjectionTheory | 111 | 73 | 65.8% | 13,357 | 9,672 | 979 | 871 | 89.0% | 2,678.00 |
| RealAnalysis | 177 | 175 | 98.9% | 2,886 | 2,224 | 149 | 147 | 98.7% | 585.64 |
| TensorCategories | 229 | 137 | 59.8% | 42,812 | 29,729 | 3,373 | 3,176 | 94.2% | 11,338.45 |
| TheoryOfComputation | 118 | 84 | 71.2% | 15,094 | 10,581 | 1,553 | 1,482 | 95.4% | 3,580.36 |
| TheoryOfProbability | 100 | 84 | 84.0% | 11,164 | 8,231 | 593 | 549 | 92.6% | 3,200.61 |
| Total | 4,007 | 2,855 | 71.3% | 630,999 | 483,917 | 46,203 | 42,837 | 92.7% | 183,157 |
The initial ATLAS effort was led by Ahmad Rammal, Niket Patel, Fabian Gloeckle, Amaury Hayat, Julia Kempe, Remi Munos, Charles Arnal, and Vivien Cabannes.
If you find this work useful, please cite our paper:
@misc{rammal2026formalizingmathematicsscale,
title={Formalizing Mathematics at Scale},
author={Ahmad Rammal and Niket Patel and Fabian Gloeckle and Amaury Hayat and Julia Kempe and Remi Munos and Charles Arnal and Vivien Cabannes},
year={2026},
eprint={2605.29955},
archivePrefix={arXiv},
primaryClass={cs.AI},
url={https://arxiv.org/abs/2605.29955},
}