Recent work on neural summarization has mainly focused on sequence-to-sequence (seq2seq) architectures (Sutskever et al., 2014), a formulation particularly suited and initially employed for abstractive summarization (Rush et al., 2015).
state-of-the-art results have been achieved by RNN-based methods which are extractive.