Text-Defend: Detecting Adversarial Examples using Local Outlier Factor
Author:
Affiliation:
1. University of Central Florida,Department of Computer Science,Orlando,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10066535/10066543/10066588.pdf?arnumber=10066588
Reference35 articles.
1. Robust Encodings: A Framework for Combating Adversarial Typos
2. Textbugger: Generating adversarial text against real-world applications;li,2018
3. TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP
4. Generating Natural Language Adversarial Examples
5. Adversarial Training with Fast Gradient Projection Method against Synonym Substitution Based Text Attacks
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