This paper presents Decomposable Neural Paraphrase Generator (DNPG), a Transformer-based model that can learn and generate paraphrases of a sentence at different levels of granularity in a disentangled way.
the model is composed of multiple encoders and decoders with different structures, each of which corresponds to a specific granularity.