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On Adversarial Examples for Text Classification by Perturbing Latent Representations
May 8, 2024, 4:41 a.m. | Korn Sooksatra, Bikram Khanal, Pablo Rivas
cs.LG updates on arXiv.org arxiv.org
Abstract: Recently, with the advancement of deep learning, several applications in text classification have advanced significantly. However, this improvement comes with a cost because deep learning is vulnerable to adversarial examples. This weakness indicates that deep learning is not very robust. Fortunately, the input of a text classifier is discrete. Hence, it can prevent the classifier from state-of-the-art attacks. Nonetheless, previous works have generated black-box attacks that successfully manipulate the discrete values of the input to …
abstract advanced advancement adversarial adversarial examples applications arxiv classification cost cs.ai cs.lg deep learning examples however improvement robust text text classification type vulnerable
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