Papers with white-box adversary

1 papers
On Adversarial Examples for Character-Level Neural Machine Translation (C18-1)

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Challenge: Using adversarial examples to measure robustness of deep learning models has become a standard procedure due to the difficulty of creating white-box adversarials for discrete text input.
Approach: They propose two novel attacks which aim to remove or change a word in a translation, rather than simply break the NMT.
Outcome: The proposed attacks are significantly stronger than their black-box counterparts in different attack scenarios, showing more serious vulnerabilities than previously known.

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