AI RESEARCH
Not All Invariants Are Equal: Curating Training Data to Accelerate Program Verification with SLMs
arXiv CS.LG
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ArXi:2603.15510v1 Announce Type: new The synthesis of inductive loop invariants is a critical bottleneck in automated program verification. While Large Language Models (LLMs) show promise in mitigating this issue, they often fail on hard instances, generating invariants that are invalid or computationally ineffective. While fine-tuning is a natural route to mitigate this limitation, obtaining high-quality