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

v1v2 (latest)

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

17 November 2020

ArXiv (abs)PDF HTML

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

5 / 5 papers shown

Title
Don't Retrain, Just Rewrite: Countering Adversarial Perturbations by Rewriting Text Ashim Gupta Carter Blum Temma Choji Yingjie Fei Shalin S Shah Alakananda Vempala Vivek Srikumar AAML 62 9 0 25 May 2023
TextShield: Beyond Successfully Detecting Adversarial Sentences in Text Classification Lingfeng Shen Ze Zhang Haiyun Jiang Ying-Cong Chen AAML 113 5 0 03 Feb 2023
ROSE: Robust Selective Fine-tuning for Pre-trained Language Models Lan Jiang Hao Zhou Yankai Lin Peng Li Jie Zhou R. Jiang AAML 84 8 0 18 Oct 2022
Improving Question Answering Performance Using Knowledge Distillation and Active Learning Yasaman Boreshban Seyed Morteza Mirbostani Gholamreza Ghassem-Sani Seyed Abolghasem Mirroshandel Shahin Amiriparian 83 16 0 26 Sep 2021
Generating Natural Adversarial Examples Zhengli Zhao Dheeru Dua Sameer Singh GAN AAML 194 601 0 31 Oct 2017