Fake News Detection via NLP is Vulnerable to Adversarial Attacks-Reference-Cited by-同舟云学术

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Fake News Detection via NLP is Vulnerable to Adversarial Attacks

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 11th International Conference on Agents and Artificial Intelligence
language:
Short-container-title:

Author:

Zhou Zhixuan¹,Guan Huankang²,Bhat Meghana³,Hsu Justin³

Affiliation:

1. Hongyi Honor College, Wuhan University, Wuhan, China, Department of Computer Science, University of Wisconsin-Madison, Madison and U.S.A., --- Select a Country ---

2. Hongyi Honor College, Wuhan University, Wuhan and China, --- Select a Country ---

3. Department of Computer Science, University of Wisconsin-Madison, Madison and U.S.A., --- Select a Country ---

Publisher

SCITEPRESS - Science and Technology Publications

Cited by 44 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Fake News in Sheep's Clothing: Robust Fake News Detection Against LLM-Empowered Style Attacks;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

2. Automatic Content Analysis Systems: Detecting Disinformation in Social Networks;Qeios;2024-05-20

3. Graph global attention network with memory: A deep learning approach for fake news detection;Neural Networks;2024-04

4. An overview of fake news detection: From a new perspective;Fundamental Research;2024-02

5. SALSA: Salience-Based Switching Attack for Adversarial Perturbations in Fake News Detection Models;Lecture Notes in Computer Science;2024

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