While reasoning over memory is appealing, these models simply choose among a set of utterances rather than generating text and also must have temporal dialogue features explicitly encoded.
the present literature lacks results for now standard sequence-to-sequence architectures, and we aim to fill this gap by building increasingly complex models of text generation, starting with a vanilla sequence-to-sequence recurrent architecture.