Papers by Huy Quang Ung

1 papers
CheckHARD: Checking Hard Labels for Adversarial Text Detection, Prediction Correction, and Perturbed Word Suggestion (2022.findings-emnlp)

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Challenge: Existing work detects adversarial text and corrects the prediction by identifying perturbed words and changing them into their synonyms, but many benign words are also changed.
Approach: They propose to detect adversarial text, correct the prediction, and suggest perturbed words by checking the change in the hard labels from the target’s predictions.
Outcome: The proposed model outperforms existing work on various attacks, models, and datasets.

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