We propose the COnditional MEmory Relation Network (COMER), a scalable and accurate dialogue state tracker that has a constant inference time complexity.
1 our model consists of an encoderdecoder network with a hierarchically stacked decoder to first generate the slot sequences in the belief state and then for each slot generate the corresponding value sequences.