Natural Language Proof

Natural language proof focuses on using large language models (LLMs) to generate and verify mathematical proofs expressed in natural language, bridging the gap between human-readable reasoning and formal logic systems. Current research emphasizes developing methods to improve the accuracy and efficiency of LLMs in this task, including techniques like contrastive decoding, verifier-guided search, and novel training datasets that align natural language proofs with formal representations. This field holds significant potential for automating proof generation and verification, assisting mathematicians and improving educational tools for teaching formal reasoning.