More recently, Generative Adversarial Net (GAN) based methods (Zang and Wan, 2017;Yu et al., 2017;Xu et al., 2018a) have been proposed to enhance the generation of long, diverse and novel text.
they still focus on word-level generation, and neglect the importance of topical and syntactic characteristics from natural languages.