Unsupervised Syntactically Controlled Paraphrase Generation with Abstract Meaning Representations

Understand

Syntactically controlled paraphrase generation has become an emerging research direction in recent years.

• Most existing approaches require annotated paraphrase pairs for training and are thus costly to extend to new domains.
• Unsupervised approaches, on the other hand, do not need paraphrase pairs but suffer from relatively poor performance in terms of syntactic control and quality of generated paraphrases.
• In this paper, we demonstrate that leveraging Abstract Meaning Representations (AMR) can greatly improve the performance of unsupervised syntactically controlled paraphrase generation.