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cs.SE2026
On the Robustness of LLMs' Internal Representation of Code Correctness
Francisco Ribeiro, Sohaila Abdulsattar, Renata Gonzalez +2
Code generated by modern language models often reads naturally. Yet, it also often fails to implement what was asked. This should be no surprise, as research shows the models' own…
cs.SE2026
On LLMs' Internal Representation of Code Correctness
Francisco Ribeiro, Claudio Spiess, Prem Devanbu +1
Despite the effectiveness of large language models (LLMs) for code generation, they often output incorrect code. One reason is that model output probabilities are often not well-co…