Papers with adversarial training modules

1 papers
TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP (2020.emnlp-demos)

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Challenge: TextAttack provides implementations of 16 adversarial attacks from the literature and supports a variety of models and datasets.
Approach: They introduce a Python framework for adversarial attacks, data augmentation, and adversarially training in NLP.
Outcome: This paper introduces a Python framework for adversarial attacks, data augmentation, and adversarially training in NLP.

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