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Sebastian Bordt
Sebastian Bordt
Verified email at uni-tuebingen.de - Homepage
Title
Cited by
Cited by
Year
Post-hoc explanations fail to achieve their purpose in adversarial contexts
S Bordt, M Finck, E Raidl, U von Luxburg
ACM Conference on Fairness, Accountability, and Transparency, 2022
442022
Chatgpt participates in a computer science exam
S Bordt, U von Luxburg
arXiv preprint arXiv:2303.09461, 2023
312023
From Shapley values to generalized additive models and back
S Bordt, U von Luxburg
International Conference on Artificial Intelligence and Statistics, 2023
202023
A bandit model for human-machine decision making with private information and opacity
S Bordt, U Von Luxburg
International Conference on Artificial Intelligence and Statistics, 2022
17*2022
Which models have perceptually-aligned gradients? an explanation via off-manifold robustness
S Srinivas, S Bordt, H Lakkaraju
Advances in neural information processing systems, 2024
52024
Estimating grouped patterns of heterogeneity in repeated public goods experiments
S Bordt, H Farbmacher, H Kögel
Working paper, 2019
52019
LLMs understand glass-box models, discover surprises, and suggest repairs
BJ Lengerich, S Bordt, H Nori, ME Nunnally, Y Aphinyanaphongs, ...
arXiv preprint arXiv:2308.01157, 2023
32023
The Manifold Hypothesis for Gradient-Based Explanations
S Bordt, U Upadhyay, Z Akata, U von Luxburg
IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2023
32023
Recovery guarantees for kernel-based clustering under non-parametric mixture models
LC Vankadara, S Bordt, U von Luxburg, D Ghoshdastidar
International Conference on Artificial Intelligence and Statistics, 2021
32021
Elephants Never Forget: Testing Language Models for Memorization of Tabular Data
S Bordt, H Nori, R Caruana
TRL Workshop at Neurips 2023, 2023
22023
Data Science with LLMs and Interpretable Models
S Bordt, B Lengerich, H Nori, R Caruana
XAI4Sci Workshop at AAAI-24, 2024
2024
Statistics without Interpretation: A Sober Look at Explainable Machine Learning
S Bordt, U von Luxburg
arXiv preprint arXiv:2402.02870, 2024
2024
Explainable Machine Learning and its Limitations
S Bordt
Universität Tübingen, 2023
2023
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