6 papers · 1 filter
Investigating Language and Retrieval Bias in Multilingual Previously Fact-Checked Claim Detection
Ivan Vykopal, Antonia Karamolegkou, Jaroslav Kopčan +4
Multilingual Large Language Models (LLMs) offer powerful capabilities for cross-lingual fact-checking. However, these models often exhibit language bias, performing disproportionat…
Automatic Fact-checking in English and Telugu
Ravi Kiran Chikkala, Tatiana Anikina, Natalia Skachkova +3
False information poses a significant global challenge, and manually verifying claims is a time-consuming and resource-intensive process. In this research paper, we experiment with…
Multilingual Political Views of Large Language Models: Identification and Steering
Daniil Gurgurov, Katharina Trinley, Ivan Vykopal +3
Large language models (LLMs) are increasingly used in everyday tools and applications, raising concerns about their potential influence on political views. While prior research has…
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…
Large Language Models for Multilingual Previously Fact-Checked Claim Detection
Ivan Vykopal, Matúš Pikuliak, Simon Ostermann +3
In our era of widespread false information, human fact-checkers often face the challenge of duplicating efforts when verifying claims that may have already been addressed in other…
Small Models, Big Impact: Efficient Corpus and Graph-Based Adaptation of Small Multilingual Language Models for Low-Resource Languages
Daniil Gurgurov, Ivan Vykopal, Josef van Genabith +1
Low-resource languages (LRLs) face significant challenges in natural language processing (NLP) due to limited data. While current state-of-the-art large language models (LLMs) stil…