AI

Compiler-Guided Adaptive Proof Search with Cross-Model Synergy on Context-Dependent Theorem Proving

Researchers from Hangfeng He and colleagues propose a new framework for theorem proving in real-world projects using Lean 4. The framework balances exploration and exploitation by generating diverse starting points through dual-model generation and resampling when progress stalls. It also refines promising proof states through compiler-grounded pairwise comparison. Experiments on seven real-world projects show that this method achieves a better tradeoff between effectiveness
Researchers from Hangfeng He and colleagues propose a new framework for theorem proving in real-world projects using Lean 4. The framework balances exploration and exploitation by generating diverse starting points through dual-model generation and resampling when progress stalls. It also refines promising proof states through compiler-grounded pairwise comparison. Experiments on seven real-world projects show that this method achieves a better tradeoff between effectiveness and efficiency compared to existing methods. --- Why it matters: This matters because theorem proving is a crucial step in software development, especially for formal verification of complex systems. This framework could improve the efficiency and accuracy of proof search, making it more practical for large-scale projects. Source: https://arxiv.org/abs/2608.18084

This article was originally published at: https://arxiv.org/abs/2608.18084