Adversarial Example Generation with Syntactically Controlled Paraphrase Networks

Understand

We propose syntactically controlled paraphrase networks (SCPNs) and use them to generate adversarial examples.

• Given a sentence and a target syntactic form (e.g., a constituency parse), SCPNs are trained to produce a paraphrase of the sentence with the desired syntax.
• We show it is possible to create training data for this task by first doing backtranslation at a very large scale, and then using a parser to label the syntactic transformations that naturally occur during this process.
• Such data allows us to train a neural encoder-decoder model with extra inputs to specify the target syntax.