AIFeb 13, 2025
Reinforced Large Language Model is a formal theorem prover
arXiv:2502.08908v1
Originality Highly original
AI Analysis
This work addresses the problem of automating theorem formalization and proof for the formal verification community, offering an incremental improvement.
The authors tackled the problem of theorem formalization and proof using Large Language Models, achieving higher accuracy through a reinforcement learning framework. The approach outperformed directly fine-tuned LLMs.
To take advantage of Large Language Model in theorem formalization and proof, we propose a reinforcement learning framework to iteratively optimize the pretrained LLM by rolling out next tactics and comparing them with the expected ones. The experiment results show that it helps to achieve a higher accuracy compared with directly fine-tuned LLM.