Specifically, once the source language is translated into the target language, CASE moves the noisy representation on the target side towards a direction of space on the source side back in a form of adversarial example, and uses this as an additional training data to task classifier.
to the best of our knowledge, we are the first proposing pseudoadversarial training in latent space for transfer learning.