Li and Hovy (2014) propose a neural network coherence model which employs distributed sentence representation and then predict the probability of whether a sequence of sentences is coherent or not.
to the methods mentioned above which learn the word relationship in or between the sentences separately, we propose a hierarchical recurrent neural network language model (HRNNLM) to capture the word sequence across the sentence boundaries at the document level.