Ivan Vykopal

Kempelen Institute of Intelligent Technologies · Natural language processing

Cross-lingual knowledge transfer, especially between high- and low-resource languages, remains a challenge in natural language processing (NLP). This study offers insights for improving cross-lingual NLP applications through the combination of parameter-efficient fine-tuning methods. We systematically explore strategies for enhancing this cross-lin...

The dissemination of false information across online platforms poses a serious societal challenge, necessitating robust measures for information verification. While manual fact-checking efforts are still instrumental, the growing volume of false information requires automated methods. Large language models (LLMs) offer promising opportunities to as...

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 developing AI-based models for multilingual disinformation analysis, addressing the tasks of rumour stance classification and claim retrieval. We describe the ExU projec...

Heart transplantation is a complex procedure, often joined with complications such as cardiac transplant rejection. Current diagnostic methods include regular invasive and time-consuming biopsies followed by histopathological analysis. Deep learning has the potential to significantly enhance speed and objectivity and introduce new information from...

Fact-checkers are often hampered by the sheer amount of online content that needs to be fact-checked. NLP can help them by retrieving already existing fact-checks relevant to the content being investigated. This paper introduces a new multilingual dataset -- MultiClaim -- for previously fact-checked claim retrieval. We collected 28k posts in 27 lan...