Existing neuralbased dialogue systems only consider this signal in a weak and implicit way, where they use hierarchical encoders to model the dialogue history (Sordoni et al., 2015a;Serban et al., 2016;Li et al., 2017;Serban et al., 2017;Xing et al., 2018).
we argue that these methods are mainly designed to model the overall semantic context information of the dialogue history but not good at modeling intermediate sequential order.