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SHIELD: Defending Textual Neural Networks against Multiple Black-Box
  Adversarial Attacks with Stochastic Multi-Expert Patcher

SHIELD: Defending Textual Neural Networks against Multiple Black-Box Adversarial Attacks with Stochastic Multi-Expert Patcher

17 November 2020
Thai Le
Noseong Park
Dongwon Lee
    AAML
ArXivPDFHTML

Papers citing "SHIELD: Defending Textual Neural Networks against Multiple Black-Box Adversarial Attacks with Stochastic Multi-Expert Patcher"

15 / 15 papers shown
Title
Better Robustness by More Coverage: Adversarial Training with Mixup
  Augmentation for Robust Fine-tuning
Better Robustness by More Coverage: Adversarial Training with Mixup Augmentation for Robust Fine-tuning
Chenglei Si
Zhengyan Zhang
Fanchao Qi
Zhiyuan Liu
Yasheng Wang
Qun Liu
Maosong Sun
AAML
SILM
42
68
0
31 Dec 2020
MALCOM: Generating Malicious Comments to Attack Neural Fake News
  Detection Models
MALCOM: Generating Malicious Comments to Attack Neural Fake News Detection Models
Thai Le
Suhang Wang
Dongwon Lee
99
59
0
01 Sep 2020
Beyond Accuracy: Behavioral Testing of NLP models with CheckList
Beyond Accuracy: Behavioral Testing of NLP models with CheckList
Marco Tulio Ribeiro
Tongshuang Wu
Carlos Guestrin
Sameer Singh
ELM
129
1,089
0
08 May 2020
Frequency-Guided Word Substitutions for Detecting Textual Adversarial
  Examples
Frequency-Guided Word Substitutions for Detecting Textual Adversarial Examples
Maximilian Mozes
Pontus Stenetorp
Bennett Kleinberg
Lewis D. Griffin
AAML
101
99
0
13 Apr 2020
Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks
Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks
Tianyu Pang
Kun Xu
Jun Zhu
AAML
47
104
0
25 Sep 2019
Combating Adversarial Misspellings with Robust Word Recognition
Combating Adversarial Misspellings with Robust Word Recognition
Danish Pruthi
Bhuwan Dhingra
Zachary Chase Lipton
114
304
0
27 May 2019
Improving Adversarial Robustness via Promoting Ensemble Diversity
Improving Adversarial Robustness via Promoting Ensemble Diversity
Tianyu Pang
Kun Xu
Chao Du
Ning Chen
Jun Zhu
AAML
57
436
0
25 Jan 2019
TextBugger: Generating Adversarial Text Against Real-world Applications
TextBugger: Generating Adversarial Text Against Real-world Applications
Jinfeng Li
S. Ji
Tianyu Du
Bo Li
Ting Wang
SILM
AAML
145
731
0
13 Dec 2018
DARTS: Differentiable Architecture Search
DARTS: Differentiable Architecture Search
Hanxiao Liu
Karen Simonyan
Yiming Yang
167
4,326
0
24 Jun 2018
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
359
921
0
21 Apr 2018
Adversarial Example Generation with Syntactically Controlled Paraphrase
  Networks
Adversarial Example Generation with Syntactically Controlled Paraphrase Networks
Mohit Iyyer
John Wieting
Kevin Gimpel
Luke Zettlemoyer
AAML
GAN
309
715
0
17 Apr 2018
Black-box Generation of Adversarial Text Sequences to Evade Deep
  Learning Classifiers
Black-box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers
Ji Gao
Jack Lanchantin
M. Soffa
Yanjun Qi
AAML
109
716
0
13 Jan 2018
Generating Natural Adversarial Examples
Generating Natural Adversarial Examples
Zhengli Zhao
Dheeru Dua
Sameer Singh
GAN
AAML
138
599
0
31 Oct 2017
Effective Approaches to Attention-based Neural Machine Translation
Effective Approaches to Attention-based Neural Machine Translation
Thang Luong
Hieu H. Pham
Christopher D. Manning
316
7,951
0
17 Aug 2015
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence
  Modeling
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
Junyoung Chung
Çağlar Gülçehre
Kyunghyun Cho
Yoshua Bengio
293
12,662
0
11 Dec 2014
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