Investigating the Efficacy of Large Language Models for Code Clone Detection. (arXiv:2401.13802v1 [cs.SE])

Large Language Models (LLMs) have demonstrated remarkable success in various natural language processing and software engineering tasks, such as code generation. The LLMs are mainly utilized in the prompt-based zero/few-shot paradigm to guide the model in accomplishing the task. %\textbf{Goal:} GPT-based models are one of the popular ones studied for tasks such as code comment generation or test generation. These tasks are generative' tasks. However, there is limited research on the usage of LLMs fornon-generative' tasks such as classification using the prompt-based paradigm. In this preliminary exploratory study, we investigated the applicability of LLMs for Code Clone Detection (CCD),

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