  Few-shot dialogue state tracking (DST) model tracks user requests in dialogue
with reliable accuracy even with a small amount of data. In this paper, we
introduce an ontology-free few-shot DST with self-feeding belief state input.
The self-feeding belief state input increases the accuracy in multi-turn
dialogue by summarizing previous dialogue. Also, we newly developed a slot-gate
auxiliary task. This new auxiliary task helps classify whether a slot is
mentioned in the dialogue. Our model achieved the best score in a few-shot
setting for four domains on multiWOZ 2.0.
