A neuro-symbolic system using LLM-guided best-first search and Isabelle tools proves up to 77.6% of theorems on the seL4 benchmark, outperforming prior LLM methods and Sledgehammer.
Hammer for coq: Automation for dependent type theory.Journal of auto- mated reasoning, 61(1):423–453, 2018
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Neuro-Symbolic Proof Generation for Scaling Systems Software Verification
A neuro-symbolic system using LLM-guided best-first search and Isabelle tools proves up to 77.6% of theorems on the seL4 benchmark, outperforming prior LLM methods and Sledgehammer.