Large Language Models for Code Summarization

2024/05/29 by Balázs Szalontai, Gergő Szalay, Szalontai, Balázs +9 · 2 citations
Computer Science · #Natural Language Processing Techniques #Topic Modeling #Web Data Mining and Analysis

paper · pdf · doi:10.48550/arxiv.2405.19032

Abstract

Recently, there has been increasing activity in using deep learning for software engineering, including tasks like code generation and summarization. In particular, the most recent coding Large Language Models seem to perform well on these problems. In this technical report, we aim to review how these models perform in code explanation/summarization, while also investigating their code generation capabilities (based on natural language descriptions).

Cited by

• CFCEval: Evaluating Security Aspects in Code Generated by Large Language Models
• InterpDetect: Interpretable Signals for Detecting Hallucinations in Retrieval-Augmented Generation

Related

• Exploring Large Language Models for Code Explanation
• Analysis on LLMs Performance for Code Summarization
• Source Code Summarization in the Era of Large Language Models
• Analyzing the Performance of Large Language Models on Code Summarization
• Automatic Semantic Augmentation of Language Model Prompts (for Code Summarization)