mlsanityData to 7 Oct 2026

Pantograph: A Machine-to-Machine Interaction Interface for Advanced Theorem Proving, High Level Reasoning, and Data Extraction in Lean 4

arXiv 2410.16429 ↗First posted 21 Oct 2024cs.LO cs.AI cs.LGcited by 15

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Abstract (arXiv)

Machine-assisted theorem proving refers to the process of conducting structured reasoning to automatically generate proofs for mathematical theorems. Recently, there has been a surge of interest in using machine learning models in conjunction with proof assistants to perform this task. In this paper, we introduce Pantograph, a tool that provides a versatile interface to the Lean 4 proof assistant and enables efficient proof search via powerful search algorithms such as Monte Carlo Tree Search. In addition, Pantograph enables high-level reasoning by enabling a more robust handling of Lean 4's inference steps. We provide an overview of Pantograph's architecture and features. We also report on an illustrative use case: using machine learning models and proof sketches to prove Lean 4 theorems. Pantograph's innovative features pave the way for more advanced machine learning models to perform complex proof searches and high-level reasoning, equipping future researchers to design more versatile and powerful theorem provers.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 10 of its 28 references that are in the map. First posted on arXiv 21 Oct 2024.

Builds on

10 of 28 references.

References · 10

  1. 2023LeanDojo: Theorem Proving with Retrieval-Augmented Language Modelscited by 414
  2. 2021MiniF2F: a cross-system benchmark for formal Olympiad-level mathematicscited by 380
  3. 2022Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofscited by 278
  4. 2022HyperTree Proof Search for Neural Theorem Provingcited by 192
  5. 2019Learning to Prove Theorems via Interacting with Proof Assistantscited by 107
  6. 2022Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Proverscited by 97
  7. 2018TacticToe: Learning to Prove with Tacticscited by 43
  8. 2020Learning to Prove Theorems by Learning to Generate Theoremscited by 43
  9. 2015A formal proof of the Kepler conjecturecited by 42
  10. 2021Graph Contrastive Pre-training for Effective Theorem Reasoningcited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 7; 2026: 8.

15 papers.

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