Lemur: Integrating Large Language Models in Automated Program Verification

Haoze Wu, Clark W. Barrett, Nina Narodytska
2/12/2026

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Abstract

The demonstrated code-understanding capability of LLMs raises the question of whether they can be used for automated program verification, a task that demands high-level abstract reasoning about program properties that is challenging for verification tools. We propose a general methodology to combine the power of LLMs and automated reasoners for automated program verification. We formally describe this methodology as a set of transition rules and prove its soundness. We instantiate the calculus as a sound automated verification procedure and demonstrate practical improvements on a set of synthetic and competition benchmarks.

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Cite this paper

@article{wu2026lemur,
  title  = {Lemur: Integrating Large Language Models in Automated Program Verification},
  author = {Haoze Wu and Clark W. Barrett and Nina Narodytska},
  year   = {2026},
  eprint = {2310.04870},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/pdf/2310.04870},
  journal = {ICLR 2023 2023}
}

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