In recent work, Zhang and Lapata (2017) propose a reinforcement learning-based text simplification model which jointly models simplicity, grammaticality, and semantic fidelity to the input.
to these methods, Narayan and Gardent (2016)'s sentence simplification approach does not need a parallel corpus for training, but rather uses a deep semantic representation as input for simplification.