Sebastian Bordt

According to our database, Sebastian Bordt authored at least 15 papers between 2020 and 2024.

Collaborative distances:

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

2024

How much can we forget about Data Contamination?

Sebastian Bordt, Suraj Srinivas, Valentyn Boreiko, Ulrike von Luxburg

CoRR, 2024

Elephants Never Forget: Memorization and Learning of Tabular Data in Large Language Models.

Sebastian Bordt, Harsha Nori, Vanessa Rodrigues, Besmira Nushi, Rich Caruana

CoRR, 2024

Elephants Never Forget: Testing Language Models for Memorization of Tabular Data.

Sebastian Bordt, Harsha Nori, Rich Caruana

CoRR, 2024

Data Science with LLMs and Interpretable Models.

Sebastian Bordt, Benjamin J. Lengerich, Harsha Nori, Rich Caruana

CoRR, 2024

Statistics without Interpretation: A Sober Look at Explainable Machine Learning.

Sebastian Bordt, Ulrike von Luxburg

CoRR, 2024

2023

Explainable Machine Learning and its Limitations.

Sebastian Bordt

PhD thesis, 2023

LLMs Understand Glass-Box Models, Discover Surprises, and Suggest Repairs.

Benjamin J. Lengerich, Sebastian Bordt, Harsha Nori, Mark E. Nunnally, Yin Aphinyanaphongs, Manolis Kellis, Rich Caruana

CoRR, 2023

ChatGPT Participates in a Computer Science Exam.

Sebastian Bordt, Ulrike von Luxburg

CoRR, 2023

Which Models have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness.

Suraj Srinivas, Sebastian Bordt, Himabindu Lakkaraju

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

The Manifold Hypothesis for Gradient-Based Explanations.

Sebastian Bordt, Uddeshya Upadhyay, Zeynep Akata, Ulrike von Luxburg

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

From Shapley Values to Generalized Additive Models and back.

Sebastian Bordt, Ulrike von Luxburg

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Post-Hoc Explanations Fail to Achieve their Purpose in Adversarial Contexts.

Sebastian Bordt, Michèle Finck, Eric Raidl, Ulrike von Luxburg

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

A Bandit Model for Human-Machine Decision Making with Private Information and Opacity.

Sebastian Bordt, Ulrike von Luxburg

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Recovery Guarantees for Kernel-based Clustering under Non-parametric Mixture Models.

Leena C. Vankadara, Sebastian Bordt, Ulrike von Luxburg, Debarghya Ghoshdastidar

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

When Humans and Machines Make Joint Decisions: A Non-Symmetric Bandit Model.

Sebastian Bordt, Ulrike von Luxburg

CoRR, 2020