Publications (8)
Rango: Adaptive Retrieval-Augmented Proving for Automated Software Verification
Kyle Thompson, Nuno Saavedra, Pedro Carrott +6
Formal verification using proof assistants, such as Coq, enables the creation of high-quality software. However, the verification process requires significant expertise and manual…
CoqPyt: Proof Navigation in Python in the Era of LLMs
Pedro Carrott, Nuno Saavedra, Kyle Thompson +3
Proof assistants enable users to develop machine-checked proofs regarding software-related properties. Unfortunately, the interactive nature of these proof assistants imposes most…
Lemmanaid: Neuro-Symbolic Lemma Conjecturing
Yousef Alhessi, Sólrún Halla Einarsdóttir, George Granberry +4
Mathematicians and computer scientists are increasingly leveraging proof assistants to formalize and check complex proofs, a task that demands substantial expertise. Can we lower t…
Getting More out of Large Language Models for Proofs
Shizhuo Dylan Zhang, Talia Ringer, Emily First
Large language models have the potential to simplify formal theorem proving and make it more accessible. But how to get the most out of these models is still an open question. To a…
Learn from Failure: Fine-Tuning LLMs with Trial-and-Error Data for Intuitionistic Propositional Logic Proving
Chenyang An, Zhibo Chen, Qihao Ye +6
Recent advances in Automated Theorem Proving have shown the effectiveness of leveraging a (large) language model that generates tactics (i.e. proof steps) to search through proof s…
Cobblestone: A Divide-and-Conquer Approach for Automating Formal Verification
Saketh Ram Kasibatla, Arpan Agarwal, Yuriy Brun +3
Formal verification using proof assistants, such as Coq, is an effective way of improving software quality, but requires significant effort and expertise. Machine learning can auto…