  The emergence of large language models (LLMs) has resulted in the production
of LLM-generated texts that is highly sophisticated and almost
indistinguishable from texts written by humans. However, this has also sparked
concerns about the potential misuse of such texts, such as spreading
misinformation and causing disruptions in the education system. Although many
detection approaches have been proposed, a comprehensive understanding of the
achievements and challenges is still lacking. This survey aims to provide an
overview of existing LLM-generated text detection techniques and enhance the
control and regulation of language generation models. Furthermore, we emphasize
crucial considerations for future research, including the development of
comprehensive evaluation metrics and the threat posed by open-source LLMs, to
drive progress in the area of LLM-generated text detection.
