Using Probabilistic Soft Logic to Improve Information Extraction in the Legal Domain. - Birgit Kirsch; Sven Giesselbach; Timothée Schmude; Malte Völkening; Frauke Rostalski; Stefan Rüping 001 (LWDA, 2020)

On the Impact of Explanations on Understanding of Algorithmic Decision-Making. - Timothée Schmude; Laura Koesten; Torsten Möller; Sebastian Tschiatschek (FAccT, 2023)

QUARE: 2nd Workshop on Measuring the Quality of Explanations in Recommender Systems. - Oana Inel; Nicolas Mattis; Milda Norkute; Alessandro Piscopo; Timothée Schmude; Sanne Vrijenhoek; Krisztian Balog (RecSys, 2023)

Applying Interdisciplinary Frameworks to Understand Algorithmic Decision-Making. - Timothée Schmude; Laura Koesten; Torsten Möller; Sebastian Tschiatschek (CoRR, 2023)

Challenging the Human-in-the-loop in Algorithmic Decision-making. - Sebastian Tschiatschek; Eugenia Stamboliev; Timothée Schmude; Mark Coeckelbergh; Laura Koesten (CoRR, 2024)

Deliberative XAI: How Explanations Impact Understanding and Decision-Making of AI Novices in Collective and Individual Settings. - Timothée Schmude; Laura Koesten; Torsten Möller; Sebastian Tschiatschek (CoRR, 2024)

Explainability and Contestability for the Responsible Use of Public Sector AI. - Timothée Schmude (CHI Extended Abstracts, 2025)

Information that matters: Exploring information needs of people affected by algorithmic decisions. - Timothée Schmude; Laura Koesten; Torsten Möller; Sebastian Tschiatschek (Int. J. Hum. Comput. Stud., 2025)

"Two Means to an End Goal": Connecting Explainability and Contestability in the Regulation of Public Sector AI. - Timothée Schmude; Mireia Yurrita; Kars Alfrink; Thomas Le Goff; Tiphaine Viard (CoRR, 2025)