  Dialogue State Tracking (DST), which is the process of inferring user goals
by estimating belief states given the dialogue history, plays a critical role
in task-oriented dialogue systems. A coreference phenomenon observed in
multi-turn conversations is not addressed by existing DST models, leading to
sub-optimal performances. In this paper, we propose Coreference Dialogue State
Tracker (CDST) that explicitly models the coreference feature. In particular,
at each turn, the proposed model jointly predicts the coreferred domain-slot
pair and extracts the coreference values from the dialogue context.
Experimental results on MultiWOZ 2.1 dataset show that the proposed model
achieves the state-of-the-art joint goal accuracy of 56.47%.
