Raising the Bar for Certified Adversarial Robustness with Diffusion
Models

Raising the Bar for Certified Adversarial Robustness with Diffusion Models

17 May 2023

Thomas Altstidl

Björn Eskofier

Papers citing "Raising the Bar for Certified Adversarial Robustness with Diffusion Models"

9 / 9 papers shown

Title
Large-Scale Dataset Pruning in Adversarial Training through Data Importance Extrapolation Bjorn Nieth Thomas Altstidl Leo Schwinn Björn Eskofier AAML 29 2 0 19 Jun 2024
Efficient Adversarial Training in LLMs with Continuous Attacks Sophie Xhonneux Alessandro Sordoni Stephan Günnemann Gauthier Gidel Leo Schwinn AAML 37 43 0 24 May 2024
Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space Leo Schwinn David Dobre Sophie Xhonneux Gauthier Gidel Stephan Gunnemann AAML 38 36 0 14 Feb 2024
1-Lipschitz Layers Compared: Memory, Speed, and Certifiable Robustness Bernd Prach Fabio Brau Giorgio Buttazzo Christoph H. Lampert 16 1 0 28 Nov 2023
$Is Certifying $\ell_p$ Robustness Still Worthwhile?$ Is Certifying $\ell_p$ Robustness Still Worthwhile? Ravi Mangal Klas Leino Zifan Wang Kai Hu Weicheng Yu Corina S. Pasareanu Anupam Datta Matt Fredrikson AAML OOD 15 1 0 13 Oct 2023
On the Design Fundamentals of Diffusion Models: A Survey Ziyi Chang G. Koulieris Hubert P. H. Shum DiffM 21 50 0 07 Jun 2023
Unlocking Deterministic Robustness Certification on ImageNet Kaiqin Hu Andy Zou Zifan Wang Klas Leino Matt Fredrikson OOD 10 12 0 29 Jan 2023
Improving Robustness against Real-World and Worst-Case Distribution Shifts through Decision Region Quantification Leo Schwinn Leon Bungert A. Nguyen René Raab Falk Pulsmeyer Doina Precup Björn Eskofier Dario Zanca OOD 42 12 0 19 May 2022
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 207 668 0 19 Oct 2020