A survey of text watermarking in the era of large language models

A Liu, L Pan, Y Lu, J Li, X Hu, X Zhang, L Wen… - ACM Computing …, 2024 - dl.acm.org
Text watermarking algorithms are crucial for protecting the copyright of textual content.
Historically, their capabilities and application scenarios were limited. However, recent …

An Overview of Large Language Models for Statisticians

W Ji, W Yuan, E Getzen, K Cho, MI Jordan… - arxiv preprint arxiv …, 2025 - arxiv.org
Large Language Models (LLMs) have emerged as transformative tools in artificial
intelligence (AI), exhibiting remarkable capabilities across diverse tasks such as text …

Can Watermarked LLMs be Identified by Users via Crafted Prompts?

A Liu, S Guan, Y Liu, L Pan, Y Zhang, L Fang… - arxiv preprint arxiv …, 2024 - arxiv.org
Text watermarking for Large Language Models (LLMs) has made significant progress in
detecting LLM outputs and preventing misuse. Current watermarking techniques offer high …

De-mark: Watermark Removal in Large Language Models

R Chen, Y Wu, J Guo, H Huang - arxiv preprint arxiv:2410.13808, 2024 - arxiv.org
Watermarking techniques offer a promising way to identify machine-generated content via
embedding covert information into the contents generated from language models (LMs) …

A Watermark for Order-Agnostic Language Models

R Chen, Y Wu, Y Chen, C Liu, J Guo… - arxiv preprint arxiv …, 2024 - arxiv.org
Statistical watermarking techniques are well-established for sequentially decoded language
models (LMs). However, these techniques cannot be directly applied to order-agnostic LMs …