Phrase-level Adversarial Example Generation for Neural Machine Translation. (arXiv:2201.02009v1 [cs.CL])

While end-to-end neural machine translation (NMT) has achieved impressive
progress, noisy input usually leads models to become fragile and unstable.
Generating adversarial examples as the augmented data is proved to be useful to
alleviate this problem. Existing methods for adversarial example generation
(AEG) are word-level or character-level. In this paper, we propose a
phrase-level adversarial example generation (PAEG) method to enhance the
robustness of the model. Our method leverages a gradient-based strategy to
substitute phrases of vulnerable positions in the …

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