Accurate attribution of authorship is crucial for maintaining the integrity of digital content,
improving forensic investigations, and mitigating the risks of misinformation and plagiarism …

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 …

During the recent years, the issue of preserving the integrity of digital text has become a
focus of interest in the transmission of online content on the Internet. Watermarking has a …

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 …

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 strong capabilities in solving diverse natural language
processing tasks. However, the safety and security issues of LLM systems have become the …

Since the remarkable generation performance of large language models raised ethical and
legal concerns, approaches to detect machine-generated text by embedding watermarks are …

The burgeoning progress in the field of Large Language Models (LLMs) heralds significant
benefits due to their unparalleled capacities. However, it is critical to acknowledge the …

The current online digital world, consisting of thousands of newspapers, blogs, social media,
and cloud file sharing services, is providing easy and unlimited access to a large treasure of …

As large language models (LLMs) generate texts with increasing fluency and realism, there
is a growing need to identify the source of texts to prevent the abuse of LLMs. Text …