This paper extends recent work examining the utility of distributed state representations for taskoriented dialogue agents, without providing rules or manually tuning features.
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.