With the rapid development and popularity of the Internet, multimedia security has become a
general essential concern. Especially, as manipulation of digital images gets much easier …

Text watermarking algorithms are crucial for protecting the copyright of textual content.
Historically, their capabilities and application scenarios were limited. However, recent …

The past 3 years of work in NLP have been characterized by the development and
deployment of ever larger language models, especially for English. BERT, its variants, GPT …

With the widespread use of large artificial intelligence (AI) models such as ChatGPT, AI-
generated content (AIGC) has garnered increasing attention and is leading a paradigm shift …

We propose a methodology for planting watermarks in text from an autoregressive language
model that are robust to perturbations without changing the distribution over text up to a …

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 …

Large language models (LLMs) have shown the ability to produce fluent and cogent content,
presenting both productivity opportunities and societal risks. To build trustworthy AI systems …

Recent advances in natural language generation have introduced powerful language
models with high-quality output text. However, this raises concerns about the potential …

Recently, machine/deep learning has become a promising solution for some intelligent
tasks. It can be actively used for watermarking but less so for conventional tasks such as …

We introduce Ghostbuster, a state-of-the-art system for detecting AI-generated text. Our
method works by passing documents through a series of weaker language models, running …