Paraphrase Generation: A Survey of the State of the Art

Abstract

This paper focuses on paraphrase generation, which is a widely studied natural language generation task in NLP. With the development of neural models, paraphrase generation research has exhibited a gradual shift to neural methods in the recent years. This has provided architectures for contextualized representation of an input text and generating fluent, diverse and human-like paraphrases. This paper surveys various approaches to paraphrase generation with a main focus on neural methods.