Simon Geisler

According to our database, Simon Geisler authored at least 28 papers between 2018 and 2025.

Collaborative distances:

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

2025

SAFT: Structure-Aware Fine-Tuning of LLMs for AMR-to-Text Generation.

Rafiq Kamel, Filippo Guerranti, Simon Geisler, Stephan Günnemann

CoRR, July, 2025

LLM-Safety Evaluations Lack Robustness.

Tim Beyer, Sophie Xhonneux, Simon Geisler, Gauthier Gidel, Leo Schwinn, Stephan Günnemann

CoRR, March, 2025

The Geometry of Refusal in Large Language Models: Concept Cones and Representational Independence.

Tom Wollschläger, Jannes Elstner, Simon Geisler, Vincent Cohen-Addad, Stephan Günnemann, Johannes Gasteiger

CoRR, February, 2025

REINFORCE Adversarial Attacks on Large Language Models: An Adaptive, Distributional, and Semantic Objective.

Simon Geisler, Tom Wollschläger, M. H. I. Abdalla, Vincent Cohen-Addad, Johannes Gasteiger, Stephan Günnemann

CoRR, February, 2025

Graph Neural Networks for Edge Signals: Orientation Equivariance and Invariance.

Dominik Fuchsgruber, Tim Postuvan, Stephan Günnemann, Simon Geisler

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Revisiting the Robust Alignment of Circuit Breakers.

Leo Schwinn, Simon Geisler

CoRR, 2024

Relaxing Graph Transformers for Adversarial Attacks.

Philipp Foth, Lukas Gosch, Simon Geisler, Leo Schwinn, Stephan Günnemann

CoRR, 2024

Explainable Graph Neural Networks Under Fire.

Zhong Li, Simon Geisler, Yuhang Wang, Stephan Günnemann, Matthijs van Leeuwen

CoRR, 2024

Attacking Large Language Models with Projected Gradient Descent.

Simon Geisler, Tom Wollschläger, M. H. I. Abdalla, Johannes Gasteiger, Stephan Günnemann

CoRR, 2024

Spatio-Spectral Graph Neural Networks.

Simon Geisler, Arthur Kosmala, Daniel Herbst, Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Poisoning × Evasion: Symbiotic Adversarial Robustness for Graph Neural Networks.

Ege Erdogan, Simon Geisler, Stephan Günnemann

CoRR, 2023

On the Adversarial Robustness of Graph Contrastive Learning Methods.

Filippo Guerranti, Zinuo Yi, Anna Starovoit, Rafiq Kamel, Simon Geisler, Stephan Günnemann

CoRR, 2023

Adversarial Training for Graph Neural Networks.

Lukas Gosch, Simon Geisler, Daniel Sturm, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann

CoRR, 2023

Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions.

Lukas Gosch, Simon Geisler, Daniel Sturm, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann

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

Transformers Meet Directed Graphs.

Simon Geisler, Yujia Li, Daniel J. Mankowitz, Ali Taylan Cemgil, Stephan Günnemann, Cosmin Paduraru

Proceedings of the International Conference on Machine Learning, 2023

Revisiting Robustness in Graph Machine Learning.

Lukas Gosch, Daniel Sturm, Simon Geisler, Stephan Günnemann

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning.

Jianxiang Feng, Jongseok Lee, Simon Geisler, Stephan Günnemann, Rudolph Triebel

Proceedings of the Conference on Robot Learning, 2023

2022

Better, Faster Small Hazard Detection: Instance-Aware Techniques, Metrics and Benchmarking.

Simon Geisler, Carlos Cunha, Ravi Kumar Satzoda

IEEE Trans. Intell. Transp. Syst., 2022

On the Robustness and Anomaly Detection of Sparse Neural Networks.

Morgane Ayle, Bertrand Charpentier, John Rachwan, Daniel Zügner, Simon Geisler, Stephan Günnemann

CoRR, 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

Are Defenses for Graph Neural Networks Robust?

Felix Mujkanovic, Simon Geisler, Stephan Günnemann, Aleksandar Bojchevski

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

Winning the Lottery Ahead of Time: Efficient Early Network Pruning.

John Rachwan, Daniel Zügner, Bertrand Charpentier, Simon Geisler, Morgane Ayle, Stephan Günnemann

Proceedings of the International Conference on Machine Learning, 2022

Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness.

Simon Geisler, Johanna Sommer, Jan Schuchardt, Aleksandar Bojchevski, Stephan Günnemann

Proceedings of the Tenth International Conference on Learning Representations, 2022

Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions.

Bertrand Charpentier, Oliver Borchert, Daniel Zügner, Simon Geisler, Stephan Günnemann

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification.

Maximilian Stadler, Bertrand Charpentier, Simon Geisler, Daniel Zügner, Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Robustness of Graph Neural Networks at Scale.

Simon Geisler, Tobias Schmidt, Hakan Sirin, Daniel Zügner, Aleksandar Bojchevski, Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Reliable Graph Neural Networks via Robust Aggregation.

Simon Geisler, Daniel Zügner, Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2018

Time-Series Features for Predictive Policing.

Julio De Melo Borges, Daniel Ziehr, Michael Beigl, Nélio Cacho, Allan de M. Martins, Adelson Araujo, Leonardo C. T. Bezerra, Simon Geisler

Proceedings of the IEEE International Smart Cities Conference, 2018