Proof-Refactor: Refactoring Generated Formal Proofs into Modular Artifacts
📰 ArXiv cs.AI
Learn to refactor generated formal proofs into modular artifacts using Proof-Refactor, improving readability and reusability
Action Steps
- Apply Proof-Refactor to generated formal proofs to identify refactoring opportunities
- Configure the refactoring pipeline to prioritize modularity and readability
- Test the refactored proofs for correctness and reusability
- Compare the refactored proofs with original generated proofs to evaluate improvements
- Run Proof-Refactor on a dataset of generated proofs to demonstrate its effectiveness
Who Needs to Know This
Researchers and developers working with Large Language Models (LLMs) and formal mathematics libraries can benefit from this approach to improve the quality and maintainability of generated proofs
Key Insight
💡 Refactoring generated formal proofs can significantly improve their quality and reusability, making them more suitable for inclusion in formal mathematics libraries
Share This
💡 Improve generated formal proofs with Proof-Refactor! Refactor for modularity, readability, and reusability #LLMs #FormalMathematics
Key Takeaways
Learn to refactor generated formal proofs into modular artifacts using Proof-Refactor, improving readability and reusability
Full Article
Title: Proof-Refactor: Refactoring Generated Formal Proofs into Modular Artifacts
Abstract:
arXiv:2606.03743v1 Announce Type: new Abstract: While Large Language Models (LLMs) have shown strong performance in generating formal proofs, their outputs often remain less readable, modular, maintainable, and reusable than proofs in mature formal mathematics libraries. We argue that this gap stems in part from the compile-first objective implicit in most proof-generation pipelines, which encourages monolithic or ad hoc proof scripts rather than library-quality artifacts. Existing approaches to
Abstract:
arXiv:2606.03743v1 Announce Type: new Abstract: While Large Language Models (LLMs) have shown strong performance in generating formal proofs, their outputs often remain less readable, modular, maintainable, and reusable than proofs in mature formal mathematics libraries. We argue that this gap stems in part from the compile-first objective implicit in most proof-generation pipelines, which encourages monolithic or ad hoc proof scripts rather than library-quality artifacts. Existing approaches to
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