3 papers
cs.CL2026
MultiCW: A Large-Scale Balanced Benchmark Dataset for Training Robust Check-Worthiness Detection Models
Martin Hyben, Sebastian Kula, Jan Cegin +3
Large Language Models (LLMs) are beginning to reshape how media professionals verify information, yet automated support for detecting check-worthy claims a key step in the fact-che…
cs.CL2025
A Generative-AI-Driven Claim Retrieval System Capable of Detecting and Retrieving Claims from Social Media Platforms in Multiple Languages
Ivan Vykopal, Martin Hyben, Robert Moro +2
Online disinformation poses a global challenge, placing significant demands on fact-checkers who must verify claims efficiently to prevent the spread of false information. A major…
cs.CL2024
ExU: AI Models for Examining Multilingual Disinformation Narratives and Understanding their Spread
Jake Vasilakes, Zhixue Zhao, Ivan Vykopal +3
Addressing online disinformation requires analysing narratives across languages to help fact-checkers and journalists sift through large amounts of data. The ExU project focuses on…