The increase of the amount of misinformation spread every day online is a huge threat to the
society. Organizations and researchers are working to contrast this misinformation plague. In …

The escalating prevalence of disinformation, or “fake news,” on social media platforms
represents a growing societal concern with far-reaching implications. Its ubiquitous …

Language models are increasingly attracting interest from writers. However, such models
lack long-range semantic coherence, limiting their usefulness for longform creative writing …

There is an important ongoing effort aimed to tackle misinformation and to perform reliable
fact-checking by employing human assessors at scale, with a crowdsourcing-based …

Automated fact-checking is often presented as an epistemic tool that fact-checkers, social
media consumers, and other stakeholders can use to fight misinformation. Nevertheless, few …

The rapid development of large language models has led to the widespread adoption of
Retrieval-Augmented Generation (RAG), which integrates external knowledge to alleviate …

The rapid entry of machine learning approaches in our daily activities and high-stakes
domains demands transparency and scrutiny of their fairness and reliability. To help gauge …

Online misinformation is posing a serious threat for the modern society. Assessing the
veracity of online information is a complex problem which nowadays is addressed by heavily …

With the evolution of social media, cyberspace has become the default medium for social
media users to communicate, especially during high-impact events such as pandemics …

Abstract Machine Learning systems rely heavily on annotated instances. Such annotations
are frequently done by human experts, or by tools developed by experts, and so the central …