27 citations · 43 across the 12 of their papers we have counts for
7 papers · 2 filters
Assessing Web Search Credibility and Response Groundedness in Chat Assistants
Ivan Vykopal, Matúš Pikuliak, Simon Ostermann +1
Chat assistants increasingly integrate web search functionality, enabling them to retrieve and cite external sources. While this promises more reliable answers, it also raises the…
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…