Increasing Confidence in Adversarial Robustness Evaluations

Increasing Confidence in Adversarial Robustness Evaluations

28 June 2022

Roland S. Zimmermann

Wieland Brendel

Florian Tramèr

Nicholas Carlini

Papers citing "Increasing Confidence in Adversarial Robustness Evaluations"

9 / 9 papers shown

Title
Testing Neural Network Verifiers: A Soundness Benchmark with Hidden Counterexamples Xingjian Zhou Hongji Xu Andy Xu Zhouxing Shi Cho-Jui Hsieh Huan Zhang AAML 70 0 0 04 Dec 2024
Optimal Zero-Shot Detector for Multi-Armed Attacks Federica Granese Marco Romanelli Pablo Piantanida AAML 29 0 0 24 Feb 2024
Calibration Attacks: A Comprehensive Study of Adversarial Attacks on Model Confidence Stephen Obadinma Xiaodan Zhu Hongyu Guo AAML 12 1 0 05 Jan 2024
Baseline Defenses for Adversarial Attacks Against Aligned Language Models Neel Jain Avi Schwarzschild Yuxin Wen Gowthami Somepalli John Kirchenbauer Ping Yeh-Chiang Micah Goldblum Aniruddha Saha Jonas Geiping Tom Goldstein AAML 10 335 0 01 Sep 2023
Are aligned neural networks adversarially aligned? Nicholas Carlini Milad Nasr Christopher A. Choquette-Choo Matthew Jagielski Irena Gao ... Pang Wei Koh Daphne Ippolito Katherine Lee Florian Tramèr Ludwig Schmidt AAML 20 221 0 26 Jun 2023
Connecting the Dots in Trustworthy Artificial Intelligence: From AI Principles, Ethics, and Key Requirements to Responsible AI Systems and Regulation Natalia Díaz Rodríguez Javier Del Ser Mark Coeckelbergh Marcos López de Prado E. Herrera-Viedma Francisco Herrera XAI 27 257 0 02 May 2023
A Minimax Approach Against Multi-Armed Adversarial Attacks Detection Federica Granese Marco Romanelli S. Garg Pablo Piantanida AAML 17 0 0 04 Feb 2023
A.I. Robustness: a Human-Centered Perspective on Technological Challenges and Opportunities Andrea Tocchetti Lorenzo Corti Agathe Balayn Mireia Yurrita Philip Lippmann Marco Brambilla Jie-jin Yang 14 10 0 17 Oct 2022
A Closer Look at Evaluating the Bit-Flip Attack Against Deep Neural Networks Kevin Hector Mathieu Dumont Pierre-Alain Moëllic J. Dutertre AAML 6 4 0 28 Sep 2022