Debiasing Vandalism Detection Models at Wikidata. - Stefan Heindorf; Yan Scholten; Gregor Engels; Martin Potthast (WWW, 2019)

CauseNet: Towards a Causality Graph Extracted from the Web. - Stefan Heindorf; Yan Scholten; Henning Wachsmuth; Axel-Cyrille Ngonga Ngomo; Martin Potthast (CIKM, 2020)

CauseNet: Towards a Causality Graph Extracted from the Web. - Stefan Heindorf; Yan Scholten; Henning Wachsmuth; Axel-Cyrille Ngonga Ngomo; Martin Potthast (Zenodo, 2020)

Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks. - Yan Scholten; Jan Schuchardt; Simon Geisler; Aleksandar Bojchevski; Stephan Günnemann (NeurIPS, 2022)

Hierarchical Randomized Smoothing. - Yan Scholten; Jan Schuchardt; Aleksandar Bojchevski; Stephan Günnemann (NeurIPS, 2023)

(Provable) Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More. - Jan Schuchardt; Yan Scholten; Stephan Günnemann (NeurIPS, 2023)

Expressivity of Graph Neural Networks Through the Lens of Adversarial Robustness. - Francesco Campi; Lukas Gosch; Tom Wollschläger; Yan Scholten; Stephan Günnemann (CoRR, 2023)

Assessing Robustness via Score-Based Adversarial Image Generation. - Marcel Kollovieh; Lukas Gosch; Yan Scholten; Marten Lienen; Stephan Günnemann (CoRR, 2023)

Assessing Robustness via Score-Based Adversarial Image Generation. - Marcel Kollovieh; Lukas Gosch; Marten Lienen; Yan Scholten; Leo Schwinn; Stephan Günnemann (Trans. Mach. Learn. Res., 2024)

Provably Reliable Conformal Prediction Sets in the Presence of Data Poisoning. - Yan Scholten; Stephan Günnemann (ICLR, 2025)

A Probabilistic Perspective on Unlearning and Alignment for Large Language Models. - Yan Scholten; Stephan Günnemann; Leo Schwinn (ICLR, 2025)

Adversarial Alignment for LLMs Requires Simpler, Reproducible, and More Measurable Objectives. - Leo Schwinn; Yan Scholten; Tom Wollschläger; Sophie Xhonneux; Stephen Casper; Stephan Günnemann; Gauthier Gidel (CoRR, 2025)

Model Collapse Is Not a Bug but a Feature in Machine Unlearning for LLMs. - Yan Scholten; Sophie Xhonneux; Leo Schwinn; Stephan Günnemann (CoRR, 2025)

Tail-aware Adversarial Attacks: A Distributional Approach to Efficient LLM Jailbreaking. - Tim Beyer; Yan Scholten; Leo Schwinn; Stephan Günnemann (CoRR, 2025)