Towards Improving Adversarial Robustness of NLP Models

Jin Yong Yoo
Adversarial training has been extensively studied as a way to improve model's adversarial robustness in computer vision. On the other hand, little attention has been paid in NLP as to how adversarial training affects model's robustness. Within NLP, there exists a significant disconnect between recent works on adversarial training and recent works on adversarial attacks as most recent works on adversarial training have studied it as a means of improving the model's generalization capability instead...
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