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  Multi-Domain Dialogue State Tracking Yexiang Wang author Yi Guo creator Siqi Zhu author 2020-nov text Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) Association for Computational
  Linguistics Online conference publication Incompleteness of domain ontology and unavailability of some
  values are two inevitable problems of dialogue state monitoring
  (DST). On this paper, we propose a new structure to cleverly
  exploit ontology, which consists of Slot Attention (SA)
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  SAS: Dialogue State Tracking via Slot Attention and Slot Information Sharing Jiaying Hu
  creator Yan Yang author Chencai Chen creator Liang
  He author Zhou Yu writer 2020-jul text Proceedings of the 58th Annual Meeting of
  the Association for Computational Linguistics Association for Computational Linguistics Online
  conference publication Dialogue state tracker is answerable for inferring person intentions by means of dialogue historical past.
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