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 …

Fact-checking has become increasingly important due to the speed with which both
information and misinformation can spread in the modern media ecosystem. Therefore …

We study the fact-checking problem, which aims to identify the veracity of a given claim.
Specifically, we focus on the task of Fact Extraction and VERification (FEVER) and its …

The wide spread of fake news is increasingly threatening both individuals and society. Great
efforts have been made for automatic fake news detection on a single domain (eg, politics) …

The prevalence and perniciousness of fake news has been a critical issue on the Internet,
which stimulates the development of automatic fake news detection in turn. In this paper, we …

Misinformation threatens modern society by promoting distrust in science, changing
narratives in public health, heightening social polarization, and disrupting democratic …

Fact verification (FV) is a challenging task which aims to verify a claim using multiple
evidential sentences from trustworthy corpora, eg, Wikipedia. Most existing approaches …

Fake news detection is crucial for preventing the dissemination of misinformation on social
media. To differentiate fake news from real ones, existing methods observe the language …

Rumors are rampant in the era of social media. Conversation structures provide valuable
clues to differentiate between real and fake claims. However, existing rumor detection …

While large pre-trained language models (LLMs) have shown their impressive capabilities in
various NLP tasks, they are still under-explored in the misinformation domain. In this paper …