DeepTextMark: A Deep Learning-Driven Text Watermarking Approach for Identifying Large Language Model Generated Text

arXiv:2305.05773v2 Announce Type: replace-cross
Abstract: The rapid advancement of Large Language Models (LLMs) has significantly enhanced the capabilities of text generators. With the potential for misuse escalating, the importance of discerning whether texts are human-authored or generated by LLMs has become paramount. Several preceding studies have ventured to address this challenge by employing binary classifiers to differentiate between human-written and LLM-generated text. Nevertheless, the reliability of these classifiers has been subject to question. Given that consequential decisions may hinge on …

abstract advancement arxiv become capabilities cs.lg cs.mm deep learning generated generators human importance language language model language models large language large language model large language models llms misuse studies text type watermarking