Adversarial Augmentation Policy Search for Domain and Cross-Lingual Generalization in Reading Comprehension

@inproceedings{Maharana2020AdversarialAP,
  title={Adversarial Augmentation Policy Search for Domain and Cross-Lingual Generalization in Reading Comprehension},
  author={Adyasha Maharana and Mohit Bansal},
  booktitle={FINDINGS},
  year={2020}
}
Reading comprehension models often overfit to nuances of training datasets and fail at adversarial evaluation. Training with adversarially augmented dataset improves robustness against those adversarial attacks but hurts generalization of the models. In this work, we present several effective adversaries and automated data augmentation policy search methods with the goal of making reading comprehension models more robust to adversarial evaluation, but also improving generalization to the source… 
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