mlsanityData to 7 Oct 2026

CoqPilot, a plugin for LLM-based generation of proofs

arXiv 2410.19605 ↗First posted 25 Oct 2024cs.SE cs.AI cs.LOcited by 10

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Abstract (arXiv)

We present CoqPilot, a VS Code extension designed to help automate writing of Coq proofs. The plugin collects the parts of proofs marked with the admit tactic in a Coq file, i.e., proof holes, and combines LLMs along with non-machine-learning methods to generate proof candidates for the holes. Then, CoqPilot checks if each proof candidate solves the given subgoal and, if successful, replaces the hole with it. The focus of CoqPilot is twofold. Firstly, we want to allow users to seamlessly combine multiple Coq generation approaches and provide a zero-setup experience for our tool. Secondly, we want to deliver a platform for LLM-based experiments on Coq proof generation. We developed a benchmarking system for Coq generation methods, available in the plugin, and conducted an experiment using it, showcasing the framework's possibilities. Demo of CoqPilot is available at: https://youtu.be/oB1Lx-So9Lo. Code at: https://github.com/JetBrains-Research/coqpilot

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 6 of its 20 references that are in the map. First posted on arXiv 25 Oct 2024.

Builds on

6 of 20 references.

References · 6

  1. 2024A Survey on Large Language Models for Code Generationcited by 646
  2. 2023Baldur: Whole-Proof Generation and Repair with Large Language Modelscited by 118
  3. 2019Learning to Prove Theorems via Interacting with Proof Assistantscited by 107
  4. 2019Generating Correctness Proofs with Neural Networkscited by 36
  5. 2020The Tactician (extended version): A Seamless, Interactive Tactic Learner and Prover for Coqcited by 23
  6. 2020QED at Large: A Survey of Engineering of Formally Verified Softwarecited by 13

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 8; 2026: 2.

10 papers.