Capturing Users' Reality: A Novel Approach to Generate Coherent Counterfactual Explanations. - Maximilian Förster; Philipp Hühn; Mathias Klier; Kilian Kluge (HICSS, 2021)

Tell Me Why (I Want It That Way) - Effects of Explanations and Online Customer Reviews on Trust in Recommender Systems. - Kilian Züllig; Eva Bohnen; Philipp Hühn; Andreas Alexander Obermeier (ICIS, 2023)

Beyond Binary Boundaries - Exploring the Potential of Categorical Variables in Counterfactual Explanations. - Philipp Hühn; Simon Hofer (Wirtschaftsinformatik, 2023)

User-centric explainable AI: design and evaluation of an approach to generate coherent counterfactual explanations for structured data. - Maximilian Förster; Philipp Hühn; Mathias Klier; Kilian Kluge (J. Decis. Syst., 2023)

Wasn't Expecting that - Using Abnormality as a Key to Design a Novel User-Centric Explainable AI Method. - Tobias Jahn; Philipp Hühn; Maximilian Förster (DESRIST, 2024)