AIBullisharXiv – CS AI · 3h ago7/10
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Functional Entropy: Predicting Functional Correctness in LLM-Generated Code with Uncertainty Quantification
Researchers demonstrate that uncertainty quantification (UQ) methods can effectively detect errors in LLM-generated code by introducing functional equivalence techniques. While token-probability methods transfer well from NLP, sampling-based approaches fail because traditional semantic models cannot distinguish functionally different code. The proposed functional entropy method outperforms existing approaches across most benchmarks.