Papers by William Macke

1 papers
Testing the Effect of Code Documentation on Large Language Model Code Understanding (2024.findings-naacl)

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Challenge: Large Language Models (LLMs) have demonstrated impressive abilities in recent years with regards to code generation and understanding.
Approach: They propose to provide an LLM with "incorrect" documentation that can greatly hinder code understanding, while incomplete or missing documentation does not seem to significantly affect an LRM's ability to understand code.
Outcome: The proposed model can generate and understand code in a language with high documentation quality while lacking documentation does not significantly affect the ability to understand code.

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