Iryna Gurevych (PhD 2003, U. Duisburg-Essen, Germany) is professor of Computer Science and director of the Ubiquitous Knowledge Processing (UKP) Lab at the Technical University (TU) of Darmstadt in Germany. In addition, she is Adjunct Professor at MBZUAI in Abu-Dhabi, UAE and Affiliated Professor at INSAIT, Sofia, Bulgaria. Her main research interests are in machine learning for large-scale language understanding and text semantics. Iryna’s work has received numerous awards such as the ACL fellow 2020, the first-ever Hessian LOEWE Distinguished Chair in 2021 (2,5 mil. Euro) and an ERC Advanced Grant in 2022 (2,5 Mil. Euro). Iryna is co-director of the NLP program within ELLIS, a European network of excellence in machine learning. In 2023, she was the president of the Association for Computational Linguistics (ACL). In 2024, she has been elected a Member of the National Academy of Science Leopoldina.

AG 1, AG 2, AG 3, INET, AG 4, AG 5, D6, SWS, RG1, MMCI   Info

AG Audience

English

60 Minutes

Kaiserslautern

Misinformation poses a growing threat to our society. It has a severe impact on public health by promoting fake cures or vaccine hesitancy, and it is used as a weapon during military conflicts to spread fear and distrust. Current natural language processing (NLP) fact-checking research focuses on identifying evidence and the veracity of a claim. People’s beliefs however often do not depend on the claim and the rational reasoning as such, but on credible content that makes the claim seem more reliable, such as scientific publications or visual content that was manipulated or stems from unrelated context. To combat misinformation we need to show (1) “Why was the claim believed to be true?”, (2) “Why is the claim false?”, (3) “Why is the alternative explanation correct?”. In the talk, I will zoom into two critical aspects of such misinformation supported by credible though misleading content. First, I will present our efforts to dismantle misleading narratives based on fallacious interpretations of scientific publications. Second, I will show how we can use multimodal large language models to (1) detect misinformation based on visual content, (2) provide strong alternative explanations for the visual content.

Geraldine Anderson

+49 631 9303 9600

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