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 …

Authorship attribution in the era of llms: Problems, methodologies, and challenges

B Huang, C Chen, K Shu - ACM SIGKDD Explorations Newsletter, 2025 - dl.acm.org
Accurate attribution of authorship is crucial for maintaining the integrity of digital content,
improving forensic investigations, and mitigating the risks of misinformation and plagiarism …

Paraphrasing evades detectors of ai-generated text, but retrieval is an effective defense

K Krishna, Y Song, M Karpinska… - Advances in Neural …, 2023 - proceedings.neurips.cc
The rise in malicious usage of large language models, such as fake content creation and
academic plagiarism, has motivated the development of approaches that identify AI …

The science of detecting LLM-generated text

R Tang, YN Chuang, X Hu - Communications of the ACM, 2024 - dl.acm.org
ACM: Digital Library: Communications of the ACM ACM Digital Library Communications of the
ACM Volume 67, Number 4 (2024), Pages 50-59 The Science of Detecting LLM-Generated Text …

Unbiased watermark for large language models

Z Hu, L Chen, X Wu, Y Wu, H Zhang… - arxiv preprint arxiv …, 2023 - arxiv.org
The recent advancements in large language models (LLMs) have sparked a growing
apprehension regarding the potential misuse. One approach to mitigating this risk is to …

On the possibilities of ai-generated text detection

S Chakraborty, AS Bedi, S Zhu, B An… - arxiv preprint arxiv …, 2023 - arxiv.org
Our work addresses the critical issue of distinguishing text generated by Large Language
Models (LLMs) from human-produced text, a task essential for numerous applications …

Who wrote this code? watermarking for code generation

T Lee, S Hong, J Ahn, I Hong, H Lee, S Yun… - arxiv preprint arxiv …, 2023 - arxiv.org
Since the remarkable generation performance of large language models raised ethical and
legal concerns, approaches to detect machine-generated text by embedding watermarks are …

A survey on the detection and impacts of deepfakes in visual, audio, and textual formats

R Mubarak, T Alsboui, O Alshaikh, I Inuwa-Dutse… - Ieee …, 2023 - ieeexplore.ieee.org
In the rapidly evolving digital landscape, the generation of fake visual, audio, and textual
content poses a significant threat to the trust of society, political stability, and integrity of …

A survey on detection of llms-generated content

X Yang, L Pan, X Zhao, H Chen, L Petzold… - arxiv preprint arxiv …, 2023 - arxiv.org
The burgeoning capabilities of advanced large language models (LLMs) such as ChatGPT
have led to an increase in synthetic content generation with implications across a variety of …

Adversarial watermarking transformer: Towards tracing text provenance with data hiding

S Abdelnabi, M Fritz - 2021 IEEE Symposium on Security and …, 2021 - ieeexplore.ieee.org
Recent advances in natural language generation have introduced powerful language
models with high-quality output text. However, this raises concerns about the potential …