Mis- and Disinformation Detection

Develop and apply LLMs for fake news and hate speech detection. Develop and utilize knowledge bases with known fakes and facts. Utilise RAGs for supporting human fact-checking tasks. Factuality analysis of generated content for summarization or knowledge enrichment.

• Sahitaj, Premtim, et al. (2025) “From Construction to Application: Advancing Argument Mining with the Large-Scale KIALOPRIME Dataset.”

• Sahitaj, Premtim, et al. (2024) “Towards Automated Fact-Checking of Real-World Claims: Exploring Task Formulation and Assessment with LLMs.” arXiv:2502.08909

• Sahitaj, Ariana, Sahitaj, Premtim, et al. (2024) “Towards a computational framework for distinguishing critical and conspiratorial texts by elaborating on the context and argumentation with LLMs.”

• Schmitt, Vera, et al. (2023) “What is your information worth? A systematic analysis of the endowment effect of different data types.”

• Jakob, Charlott, et al. (2024) “Augmented Political Leaning Detection: Leveraging Parliamentary Speeches for Classifying News Articles.”

• Jakob, Charlott, et al. (2024) “Classifying Sustainability Reports Using Companies Self-Assessments.”

• Schmitt, Vera, et al. (2024) “Evaluating Human-Centered AI Explanations: Introduction of an XAI evaluation framework for fact-checking.”