To solve the out-of-vocabulary (OOV) problem, conventional Seq2Seq models utilize a copy mechanism (Gu et al., 2016) that selects a word from source (complex) sentence directly with a trainable pointer.
editNTS has the ability to copy OOV words into the simplified sentences by directly learning to predict KeeP on them in complex sentences.