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2021

Grey-box Adversarial Attack And Defence For Sentiment Classification

Xu, Ying, Zhong, Xu, Yepes, Antonio Jimeno et al.

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We introduce a grey-box adversarial attack and defence framework for sentiment classification.

We address the issues of differentiability, label preservation and input reconstruction for adversarial attack and defence in one unified framework.
Our results show that once trained, the attacking model is capable of generating high-quality adversarial examples substantially faster (one order of magnitude less in time) than state-of-the-art attacking methods.
These examples also preserve the original sentiment according to human evaluation.

Grey-box Adversarial Attack And Defence For Sentiment Classification · Around

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