A neuro-symbolic post-training pipeline lets a 4B transformer learn cubing heuristics that reach pass@5 of 53 on 100 SAT competition instances, matching the strongest symbolic baseline.
arXiv preprint arXiv:2410.07432 , year =
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LLMs, verified by a symbolic model checker, produced correct inductive strengthenings for 82 of 94 curated RTL safety properties.
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Learning How to Cube
A neuro-symbolic post-training pipeline lets a 4B transformer learn cubing heuristics that reach pass@5 of 53 on 100 SAT competition instances, matching the strongest symbolic baseline.
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Large Lemma Miners: Can LLMs do Induction Proofs for Hardware?
LLMs, verified by a symbolic model checker, produced correct inductive strengthenings for 82 of 94 curated RTL safety properties.