The rapid advancement of large language models (LLMs), such as ChatGPT and GPT-4, has led to a surge in synthetic text generation across various domains, including journalism, academia, cybersecurity, and online discourse. While these models offer immense benefits, their ability to generate highly realistic text raises concerns regarding misinformation, academic dishonesty, and content authenticity. Consequently, the detection of LLM-generated content has become an essential area of research.

This survey provides a comprehensive overview of existing detection methodologies, benchmarks, and challenges, offering insights into the strengths and weaknesses of current techniques.The study aims to serve as a guiding reference for researchers and practitioners striving to uphold the integrity of digital information in an era dominated by synthetic content.

📁 Paper: https://arxiv.org/abs/2310.15654

@scopeofai
@LLM_learning