CoqPilot, a plugin for LLM-based generation of proofs
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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
- 2024A Survey on Large Language Models for Code Generationcited by 646
- 2023Baldur: Whole-Proof Generation and Repair with Large Language Modelscited by 118
- 2019Learning to Prove Theorems via Interacting with Proof Assistantscited by 107
- 2019Generating Correctness Proofs with Neural Networkscited by 36
- 2020The Tactician (extended version): A Seamless, Interactive Tactic Learner and Prover for Coqcited by 23
- 2020QED at Large: A Survey of Engineering of Formally Verified Softwarecited by 13
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Citing papers per year: 2025: 8; 2026: 2.
10 papers.
- 2025A Contemporary Survey of Large Language Model Assisted Program Analysiscited by 10
- 2025LeanProgress: Guiding Search for Neural Theorem Proving via Proof Progress Predictioncited by 9
- 2025Locus: Agentic Predicate Synthesis for Directed Fuzzingcited by 8
- 2025RocqStar: Leveraging Similarity-driven Retrieval and Agentic Systems for Rocq generationcited by 3
- 2025A Case Study on the Effectiveness of LLMs in Verification with Proof Assistantscited by 3
- 2025Building A Proof-Oriented Programmer That Is 64% Better Than GPT-4o Under Data Scarcitycited by 2
- 2025ProofWala: A Framework for Multilingual Proof Data Synthesis and Theorem-Provingcited by 1
- 2026RocqSmith: Can Automatic Optimization Forge Better Proof Agents?cited by 1
- 2026AoA: Theorem Proving Agent over Abstract Syntax Tree of Redesigned Languagecited by 1
- 2025Position: Intelligent Coding Systems Should Write Programs with Justificationscited by 0
- 2026AoA: Theorem Proving Agent over Abstract Syntax Tree of Redesigned Language17 Jul 2026
- 2026RocqSmith: Can Automatic Optimization Forge Better Proof Agents?5 Feb 2026
- 2025Locus: Agentic Predicate Synthesis for Directed Fuzzing29 Aug 2025
- 2025A Case Study on the Effectiveness of LLMs in Verification with Proof Assistants26 Aug 2025
- 2025Position: Intelligent Coding Systems Should Write Programs with Justifications8 Aug 2025
- 2025RocqStar: Leveraging Similarity-driven Retrieval and Agentic Systems for Rocq generation28 May 2025
- 2025LeanProgress: Guiding Search for Neural Theorem Proving via Proof Progress Prediction25 Feb 2025
- 2025Building A Proof-Oriented Programmer That Is 64% Better Than GPT-4o Under Data Scarcity17 Feb 2025
- 2025ProofWala: A Framework for Multilingual Proof Data Synthesis and Theorem-Proving7 Feb 2025
- 2025A Contemporary Survey of Large Language Model Assisted Program Analysis5 Feb 2025