NeSy is alive and well: A LLM-driven symbolic approach for better code comment data generation and classification
<|reference_start|>NeSy is alive and well: A LLM-driven symbolic approach for better code comment data generation and classification: We present a neuro-symbolic (NeSy) workflow combining a symbolic-based learning technique with a large language model (LLM) agent to generate synthetic data for code comment classification in the C programming language. We also show how generating controlled synthetic data using this workflow fixes some of the notable weaknesses of LLM-based generation and increases the performance of classical machine learning models on the code comment classification task. Our best model, a Neural Network, achieves a Macro-F1 score of 91.412% with an increase of 1.033% after data augmentation.<|reference_end|>
@article{akl2024nesy,
    title={NeSy is alive and well: A LLM-driven symbolic approach for better code
  comment data generation and classification},
    author={Hanna Abi Akl},
    journal={arXiv preprint arXiv:2402.16910},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.16910},
    primaryClass={cs.SE cs.AI}
}