A Survey of Text Watermarking in the Era of Large Language Models
Overview of text watermarking in the era of LLMsThis survey paper provides a comprehensive overview of text watermarking technology in the era of Large Language Models (LLMs). The work covers four main aspects:
Text Watermarking Techniques: A detailed overview and comparison of different text watermarking methods, including their strengths and limitations.
Evaluation Methods: Analysis of how to evaluate text watermarking algorithms, focusing on:
- Detectability
- Impact on text quality
- Impact on LLM performance
- Robustness against targeted and untargeted attacks
Application Scenarios: Exploration of potential use cases for text watermarking technology, particularly in the context of LLM-generated content.
Challenges and Future Directions: Discussion of current limitations and promising research directions in the field.
The survey aims to provide researchers with a thorough understanding of text watermarking technology in the LLM era, helping to advance the field and protect intellectual property in the age of AI-generated content.