Fine-tuned GPT-4.1-mini reaches 0.9072 static similarity and 92.5% functional correctness on a new synthetic dataset of cryptographic code migrations, outperforming zero-shot baselines.
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Derives pass bounds for confirmation-code-augmented FO KEM tests and proves α+β≥1 lower bound on certifier errors under honest-support harnesses that factor through final-key targets.
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Empirical Evaluation of Large Language Models for Migration of Code Fragments to Post-Quantum Cryptography
Fine-tuned GPT-4.1-mini reaches 0.9072 static similarity and 92.5% functional correctness on a new synthetic dataset of cryptographic code migrations, outperforming zero-shot baselines.