3 citations · 3 across the 1 of their papers we have counts for
7 papers
Generative Large Language Models in Automated Fact-Checking: A Survey
Ivan Vykopal, Matúš Pikuliak, Simon Ostermann +1
The rapid spread of false and misleading information on online platforms poses a growing societal challenge, overwhelming the capacity of manual fact-checking and increasing the de…
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…
DelTriC: A Novel Clustering Method with Accurate Outlier
Tomas Javurek, Michal Gregor, Sebastian Kula +1
The paper introduces DelTriC (Delaunay Triangulation Clustering), a clustering algorithm which integrates PCA/UMAP-based projection, Delaunay triangulation, and a novel back-projec…
Investigating Language and Retrieval Bias in Multilingual Previously Fact-Checked Claim Detection
Ivan Vykopal, Antonia Karamolegkou, Jaroslav KopÄan +4
Multilingual Large Language Models (LLMs) offer powerful capabilities for cross-lingual fact-checking. However, these models often exhibit language bias, performing disproportionat…
SemEval-2025 Task 7: Multilingual and Crosslingual Fact-Checked Claim Retrieval
Qiwei Peng, Robert Moro, Michal Gregor +7
The rapid spread of online disinformation presents a global challenge, and machine learning has been widely explored as a potential solution. However, multilingual settings and low…
Soft Language Prompts for Language Transfer
Ivan Vykopal, Simon Ostermann, Marián Šimko
Cross-lingual knowledge transfer, especially between high- and low-resource languages, remains challenging in natural language processing (NLP). This study offers insights for impr…