A systematic study shows that an LLM's internal code-correctness signal depends strongly on extraction configuration and fitting data, and that mutation-isolated bugs do not transfer to ranking real candidates.
An automated methodol- ogy for generating labeled datasets of semantic errors in code,
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On the Robustness of LLMs' Internal Representation of Code Correctness
A systematic study shows that an LLM's internal code-correctness signal depends strongly on extraction configuration and fitting data, and that mutation-isolated bugs do not transfer to ranking real candidates.