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RobustBench: a standardized adversarial robustness benchmark

RobustBench: a standardized adversarial robustness benchmark

19 October 2020
Francesco Croce
Maksym Andriushchenko
Vikash Sehwag
Edoardo Debenedetti
Nicolas Flammarion
M. Chiang
Prateek Mittal
Matthias Hein
    VLM
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Papers citing "RobustBench: a standardized adversarial robustness benchmark"

13 / 163 papers shown
Title
Relating Adversarially Robust Generalization to Flat Minima
Relating Adversarially Robust Generalization to Flat Minima
David Stutz
Matthias Hein
Bernt Schiele
OOD
32
65
0
09 Apr 2021
Fixing Data Augmentation to Improve Adversarial Robustness
Fixing Data Augmentation to Improve Adversarial Robustness
Sylvestre-Alvise Rebuffi
Sven Gowal
D. A. Calian
Florian Stimberg
Olivia Wiles
Timothy A. Mann
AAML
36
269
0
02 Mar 2021
Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints
Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints
Maura Pintor
Fabio Roli
Wieland Brendel
Battista Biggio
AAML
43
70
0
25 Feb 2021
Bridging the Gap Between Adversarial Robustness and Optimization Bias
Bridging the Gap Between Adversarial Robustness and Optimization Bias
Fartash Faghri
Sven Gowal
C. N. Vasconcelos
David J. Fleet
Fabian Pedregosa
Nicolas Le Roux
AAML
192
7
0
17 Feb 2021
On the Paradox of Certified Training
On the Paradox of Certified Training
Nikola Jovanović
Mislav Balunović
Maximilian Baader
Martin Vechev
OOD
28
13
0
12 Feb 2021
RoBIC: A benchmark suite for assessing classifiers robustness
RoBIC: A benchmark suite for assessing classifiers robustness
Thibault Maho
Benoît Bonnet
Teddy Furon
Erwan Le Merrer
AAML
21
4
0
10 Feb 2021
Recent Advances in Understanding Adversarial Robustness of Deep Neural
  Networks
Recent Advances in Understanding Adversarial Robustness of Deep Neural Networks
Tao Bai
Jinqi Luo
Jun Zhao
AAML
46
8
0
03 Nov 2020
SoK: Certified Robustness for Deep Neural Networks
SoK: Certified Robustness for Deep Neural Networks
Linyi Li
Tao Xie
Bo-wen Li
AAML
30
128
0
09 Sep 2020
Systematic Evaluation of Privacy Risks of Machine Learning Models
Systematic Evaluation of Privacy Risks of Machine Learning Models
Liwei Song
Prateek Mittal
MIACV
196
358
0
24 Mar 2020
FreeLB: Enhanced Adversarial Training for Natural Language Understanding
FreeLB: Enhanced Adversarial Training for Natural Language Understanding
Chen Zhu
Yu Cheng
Zhe Gan
S. Sun
Tom Goldstein
Jingjing Liu
AAML
226
438
0
25 Sep 2019
Generating Natural Language Adversarial Examples
Generating Natural Language Adversarial Examples
M. Alzantot
Yash Sharma
Ahmed Elgohary
Bo-Jhang Ho
Mani B. Srivastava
Kai-Wei Chang
AAML
245
914
0
21 Apr 2018
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
234
1,837
0
03 Feb 2017
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
287
5,837
0
08 Jul 2016
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