Less is More: Understanding Word-level Textual Adversarial Attack via n-gram Frequency Descend-Reference-Cited by-同舟云学术

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Less is More: Understanding Word-level Textual Adversarial Attack via n-gram Frequency Descend

Published:2024-06-25 Issue: Volume:abs/1702.08138 Page:823-830
ISSN:
Container-title:2024 IEEE Conference on Artificial Intelligence (CAI)
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Author:

Lu Ning¹,Liu Shengcai²,Zhang Zhirui³,Wang Qi⁴,Liu Haifeng⁵,Tang Ke¹

Affiliation:

1. Southern University of Science and Technology,Guangdong Key Laboratory of Brain-Inspired Intelligent Computation,Department of Computer Science and Engineering

2. Agency for Science, Technology and Research,Centre for Frontier AI Research

3. Tencent AI Lab

4. Southern University of Science and Technology,Department of Computer Science and Engineering

5. OPPO Mobile Telecommunications Corp.

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10605128/10605229/10605391.pdf?arnumber=10605391

Reference55 articles.

1. Explaining and harnessing adversarial examples;Goodfellow

2. Crafting adversarial input sequences for recurrent neural networks

3. Black-Box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers

4. TextBugger: Generating Adversarial Text Against Real-world Applications

5. Generating Natural Language Adversarial Examples

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