Papers with untargeted adversarial training

1 papers
On Evaluation of Adversarial Perturbations for Sequence-to-Sequence Models (N19-1)

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Challenge: Existing methods for assessing the robustness of sequence-to-sequence models have been ignored by the literature.
Approach: They propose an evaluation framework for adversarial attacks on seq2seq models that takes the semantic equivalence of the pre- and post-perturbation input into account.
Outcome: The proposed framework breaks the assumption that source perturbations should not result in changes in the expected output, but allows for meaning-preserving perturbations that change the output sequence.

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