Large Language Models (LLMs) went from non-existent to ubiquitous in the machine
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …

Machine-generated text is increasingly difficult to distinguish from text authored by humans.
Powerful open-source models are freely available, and user-friendly tools that democratize …

The increasing fluency and widespread usage of large language models (LLMs) highlight
the desirability of corresponding tools aiding detection of LLM-generated text. In this paper …

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 …

Human evaluations are typically considered the gold standard in natural language
generation, but as models' fluency improves, how well can evaluators detect and judge …

The advent of Large Language Models (LLMs) has made a transformative impact. However,
the potential that LLMs such as ChatGPT can be exploited to generate misinformation has …

Text generative models (TGMs) excel in producing text that matches the style of human
language reasonably well. Such TGMs can be misused by adversaries, eg, by automatically …

Nowadays, powerful large language models (LLMs) such as ChatGPT have demonstrated
revolutionary power in a variety of tasks. Consequently, the detection of machine-generated …

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 …

With the rapid progress of large language models (LLMs) and the huge amount of text they
generated, it becomes more and more impractical to manually distinguish whether a text is …