This paper introduces Lastde, a novel training-free method for detecting LLM-generated text by analyzing the temporal dynamics of token probability sequences using diversity entropy, achieving state-of-the-art performance in both white-box and black-box settings.
Detecting text generated by large language models (LLMs) is crucial to mitigate potential misuse and safeguard realms like artistic expression and social networks from harmful influence of LLM-generated content.