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Found 5 papers, 2 papers with code
Lemmanaid: Neuro-Symbolic Lemma Conjecturing
We train an LLM to generate lemma templates that describe the shape of a lemma, and use symbolic methods to fill in the details.
Rango: Adaptive Retrieval-Augmented Proving for Automated Software Verification
We present Rango, a fully automated proof synthesis tool for Coq that automatically identifies relevant premises and also similar proofs from the current project and uses them during synthesis.
Cobblestone: Iterative Automation for Formal Verification
We introduce Cobblestone, a new proof-synthesis approach that improves on the state of the art by taking advantage of partial progress in proof synthesis attempts.
Learn from Failure: Fine-Tuning LLMs with Trial-and-Error Data for Intuitionistic Propositional Logic Proving
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 states.
Baldur: Whole-Proof Generation and Repair with Large Language Models
Recent work has developed methods to automate formal verification using proof assistants, such as Coq and Isabelle/HOL, e. g., by training a model to predict one proof step at a time, and using that model to search through the space of possible proofs.
