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The Lean mathematical library

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arxiv 1910.09336 v2 pith:OIP547UN submitted 2019-10-21 cs.LO math.LO

classification cs.LOmath.LO
keywords libraryassistantleanmathematicsorganizationproofarchitectureautomation
verification ladder T0 review T1 audit T2 compute T3 formal
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This paper describes mathlib, a community-driven effort to build a unified library of mathematics formalized in the Lean proof assistant. Among proof assistant libraries, it is distinguished by its dependently typed foundations, focus on classical mathematics, extensive hierarchy of structures, use of large- and small-scale automation, and distributed organization. We explain the architecture and design decisions of the library and the social organization that has led us here.

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Cited by 9 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Beyond the Library: An Agentic Framework for Autoformalizing Research Mathematics

    cs.AI 2026-06 conditional novelty 7.0 of 10

    Agentic LLM framework autoformalizes 32 Putnam problems and main theorems plus proofs from five STOC papers into Lean 4, with two proofs using only kernel axioms.

  2. Beyond the Library: An Agentic Framework for Autoformalizing Research Mathematics

    cs.AI 2026-06 accept novelty 7.0 of 10

    An orchestrator-driven agentic pipeline using general coding LLMs autoformalizes 32 PutnamBench problems and the main theorems plus proofs from five STOC papers into Lean 4, with two proofs using only the kernel.

  3. Formalizing Mathematics at Scale

    cs.AI 2026-05 accept novelty 7.0 of 10

    A multi-agent framework called AutoformBot autoformalized 26 textbooks spanning analysis, algebra, topology, combinatorics and probability into a verified Lean 4 library of 45k declarations, demonstrating scalable for...

  4. Nazrin: An Atomic Neural Proof Automation Tactic in Lean 4

    cs.LO 2026-02 conditional novelty 7.0 of 10

    A finite set of atomic Lean tactics plus a transposing atomization algorithm lets a small graph neural network, Nazrin, be trained on converted proofs and prove held-out formal theorems.

  5. To Throw a Stone with Six Birds: On Agents and Agenthood

    cs.AI 2026-02 unverdicted novelty 7.0 of 10

    Six Birds Theory defines agents as maintained theory objects with feasible policies that make counterfactual differences, operationalized via ledger feasibility, viability kernels, empowerment, and packaging maps, and...

  6. Proof-Refactor: Refactoring Generated Formal Proofs into Modular Artifacts

    cs.AI 2026-06 unverdicted novelty 6.0 of 10

    Proof-Refactor is a four-phase agentic system that refactors LLM-generated Lean proofs from PutnamBench and Putnam2025 into more modular forms, outperforming a Claude Code baseline on rubric scores for signature quali...

  7. Exploring Formal Math on the Blockchain: An Explorer for Proofgold

    cs.LO 2025-09 accept novelty 6.0 of 10

    The authors present the first web explorer for the Proofgold formal-math blockchain, including case studies of category theory formalizations.

  8. Optimizing the Cost-Quality Tradeoff of Agentic Theorem Provers in Lean

    cs.CL 2026-06 unverdicted novelty 5.0 of 10

    An agentic theorem prover in Lean uses a control plane to route actions based on cost and success estimates, achieving 28.9% lower average cost than a fixed-step baseline on a PutnamBench subset while preserving performance.

  9. Saturating Scaling Laws for Equational Discovery: A Phenomenology of Growth Dynamics in Three Toy Substrates with Two Real-World Replications

    cs.AI 2026-05 unverdicted novelty 4.0 of 10

    Growth of equational discoveries follows power laws whose exponent and saturation behavior are conditional on the substrate, with a heuristic saturating model fitting some real-world cases better than pure power laws.

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