Code Documentation Generation
6 papers with code • 7 benchmarks • 5 datasets
Code Documentation Generation is a supervised task where a code function is the input to the model, and the model generates the documentation for this function.
Description from: CodeTrans: Towards Cracking the Language of Silicone's Code Through Self-Supervised Deep Learning and High Performance Computing
Benchmarks
These leaderboards are used to track progress in Code Documentation Generation
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CodeSearchNet
Latest papers with no code
A Comparative Analysis of Large Language Models for Code Documentation Generation
The paper evaluates models such as GPT-3. 5, GPT-4, Bard, Llama2, and Starchat on various parameters like Accuracy, Completeness, Relevance, Understandability, Readability and Time Taken for different levels of code documentation.
