Mirror Minds : An Empirical Study on Detecting LLM-Generated Text via LLMs

AbstractThe use of large language models (LLMs) is inevitable in text generation. LLMs are intelligent and slowly replacing the search engines. LLMs became the de facto choice for conversation, knowledge extraction, and brain storming. This study focuses on a question: ‘Can we utilize the generative capabilities of LLMs to detect AI-generated content?’ We present a methodology and empirical results on four publicly available data sets. The result shows, with 90% accuracy it is possible to detect AI-generated content by a zero-shot detector utilizing multiple LLMs.