arXiv Machine Learning By Zhipeng Cao, Peiyang Song, Nikolaus Vertovec, Weiru Cui, Zhihao Yang, Mingkang Liu, Luxia Lin, Bai Xue, Alessandro Abate

LLM2Cert: LLM Synthesis of Certificates with SMT/Lean Verification

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The paper introduces DynaCertBench, a benchmark of 105 diverse systems for certifying stability, safety, and related properties, and presents LLM2Cert, a framework that uses large language models to generate and verify candidate certificates via SMT solvers or Lean. LLM2Cert achieves a 77.1% verification rate on the benchmark, improving by 17.1 percentage points over a single-shot approach, and successfully verifies 22 certificates that All-SMT could not resolve. The authors provide code and data on GitHub for reproducibility.

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