Yan Scholten

According to our database, Yan Scholten authored at least 14 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Tail-aware Adversarial Attacks: A Distributional Approach to Efficient LLM Jailbreaking.

Tim Beyer, Yan Scholten, Leo Schwinn, Stephan Günnemann

CoRR, July, 2025

Model Collapse Is Not a Bug but a Feature in Machine Unlearning for LLMs.

Yan Scholten, Sophie Xhonneux, Leo Schwinn, Stephan Günnemann

CoRR, July, 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, February, 2025

A Probabilistic Perspective on Unlearning and Alignment for Large Language Models.

Yan Scholten, Stephan Günnemann, Leo Schwinn

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Provably Reliable Conformal Prediction Sets in the Presence of Data Poisoning.

Yan Scholten, Stephan Günnemann

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

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

2023

Assessing Robustness via Score-Based Adversarial Image Generation.

Marcel Kollovieh, Lukas Gosch, Yan Scholten, Marten Lienen, Stephan Günnemann

CoRR, 2023

Expressivity of Graph Neural Networks Through the Lens of Adversarial Robustness.

Francesco Campi, Lukas Gosch, Tom Wollschläger, Yan Scholten, Stephan Günnemann

CoRR, 2023

(Provable) Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More.

Jan Schuchardt, Yan Scholten, Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Hierarchical Randomized Smoothing.

Yan Scholten, Jan Schuchardt, Aleksandar Bojchevski, Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks.

Yan Scholten, Jan Schuchardt, Simon Geisler, Aleksandar Bojchevski, Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2020

CauseNet: Towards a Causality Graph Extracted from the Web.

Stefan Heindorf, Yan Scholten, Henning Wachsmuth, Axel-Cyrille Ngonga Ngomo, Martin Potthast

Dataset, October, 2020

CauseNet: Towards a Causality Graph Extracted from the Web.

Stefan Heindorf, Yan Scholten, Henning Wachsmuth, Axel-Cyrille Ngonga Ngomo, Martin Potthast

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2019

Debiasing Vandalism Detection Models at Wikidata.

Stefan Heindorf, Yan Scholten, Gregor Engels, Martin Potthast

Proceedings of the World Wide Web Conference, 2019