Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis
Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. However, research has shown that the adversarial vulnerabilities of deep learning networks...
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| Other Authors: | , , , , , |
| Format: | article |
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2023
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| Online Access: | http://dx.doi.org/10.1016/j.cose.2023.103367 https://www.sciencedirect.com/science/article/pii/S0167404823002778 http://hdl.handle.net/10576/65987 |
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