In particular, the bidirectional LSTM is first adopted as a sentence encoder to map the input sentences to the corresponding distributed vectors, and then a self-attention based paragraph encoder is introduced to capture structural relationships across sentences and to obtain a hierarchical context representation of the entire set of sentences.
based on the learned paragraph vector, a pointer network is applied to perform sentence ordering by decoding an ordered sequence.