The proposed model ignores long-range dependencies that could conceivably be captured using alternative architectures, such as recurrent neural networks (RNN) (Mikolov et al., 2010;Luong et al., 2013).
topical and stylistic information is contained in shorter word and character sequences for which the shallow neural network architectures with n-gram feature representations are likely to be sufficient, while having the advantage of being much faster to run.