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A Semantic Search Engine for Mathlib4

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arxiv 2403.13310 v2 pith:FQH3PJUJ submitted 2024-03-20 cs.IR cs.LGcs.LO

classification cs.IRcs.LGcs.LO
keywords mathlib4searchenginemathematicalsemanticexpandingtheoremsaccepts
verification ladder T0 review T1 audit T2 compute T3 formal

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The interactive theorem prover Lean enables the verification of formal mathematical proofs and is backed by an expanding community. Central to this ecosystem is its mathematical library, mathlib4, which lays the groundwork for the formalization of an expanding range of mathematical theories. However, searching for theorems in mathlib4 can be challenging. To successfully search in mathlib4, users often need to be familiar with its naming conventions or documentation strings. Therefore, creating a semantic search engine that can be used easily by individuals with varying familiarity with mathlib4 is very important. In this paper, we present a semantic search engine (https://leansearch.net/) for mathlib4 that accepts informal queries and finds the relevant theorems. We also establish a benchmark for assessing the performance of various search engines for mathlib4.

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Cited by 4 Pith papers

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

  1. Aria: An Agent For Retrieval and Iterative Auto-Formalization via Dependency Graph

    cs.AI 2025-10 conditional novelty 6.0 of 10

    A graph-of-thought agent with retrieval and a term-grounded semantic checker auto-formalizes research-level math statements in Lean, hitting 68.5% on ProofNet and 6/14 homological conjectures where baselines score 0.

  2. Tutte's theorem as an educational formalization project

    cs.LO 2025-04 conditional novelty 6.0 of 10

    A Lean formalization of Tutte's theorem is presented and contributed to mathlib, together with a two-phase framework for educational formalization projects.

  3. Integrating Rules and Semantics for LLM-Based C-to-Rust Translation

    cs.SE 2025-08 unverdicted novelty 5.0 of 10

    IRENE combines rule-based retrieval, structured summarization, and compiler feedback to improve LLM-based C-to-Rust translation accuracy and safety.

  4. Formal Mathematical Reasoning: A New Frontier in AI

    cs.AI 2024-12 conditional novelty 5.0 of 10

    Machine-checkable formal proof should become the backbone of AI mathematics, and a five-task, five-level capability roadmap can measure progress toward that goal.

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