Proof System
Proof systems are formal frameworks for verifying the validity of mathematical statements and logical arguments, aiming to automate or assist in the process of proof construction and verification. Current research focuses on improving the efficiency and scalability of proof systems through novel algorithms like Expected Work Search and the integration of machine learning techniques, including transformer-based models and graph neural networks, to enhance proof discovery and recommendation. These advancements have implications for various fields, including automated theorem proving, formal verification of software and hardware, and even assisting in educational settings by providing automated feedback on student proofs.
Papers
MathGAP: Out-of-Distribution Evaluation on Problems with Arbitrarily Complex Proofs
Andreas Opedal, Haruki Shirakami, Bernhard Schölkopf, Abulhair Saparov, Mrinmaya Sachan
Proof Flow: Preliminary Study on Generative Flow Network Language Model Tuning for Formal Reasoning
Matthew Ho, Vincent Zhu, Xiaoyin Chen, Moksh Jain, Nikolay Malkin, Edwin Zhang