Theorem Provers
Theorem provers are automated systems designed to verify mathematical proofs and logical arguments, aiming to enhance the reliability and efficiency of reasoning processes. Current research focuses on integrating theorem provers with large language models (LLMs), creating hybrid neuro-symbolic architectures that leverage the strengths of both symbolic reasoning and natural language processing. This integration addresses limitations in LLMs' logical consistency and allows for more robust and interpretable reasoning, particularly in complex domains like mathematics and formal verification. The resulting advancements have significant implications for various fields, including AI safety, formal verification of software and hardware, and the development of more trustworthy AI systems.
Papers
Pantograph: A Machine-to-Machine Interaction Interface for Advanced Theorem Proving, High Level Reasoning, and Data Extraction in Lean 4
Leni Aniva, Chuyue Sun, Brando Miranda, Clark Barrett, Sanmi Koyejo
Alchemy: Amplifying Theorem-Proving Capability through Symbolic Mutation
Shaonan Wu, Shuai Lu, Yeyun Gong, Nan Duan, Ping Wei