NeSy is alive and well: A LLM-driven symbolic approach for better code comment data generation and classification

• URL: http://arxiv.org/abs/2402.16910v2
• Date: Fri, 24 May 2024 07:11:17 GMT
• Title: NeSy is alive and well: A LLM-driven symbolic approach for better code comment data generation and classification
• Authors: Hanna Abi Akl,
• Abstract summary: 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. Our best model, a Neural Network, achieves a Macro-F1 score of 91.412% with an increase of 1.033% after data augmentation.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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