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  Slot Attention with Value Normalization for Multi-Domain Dialogue State Tracking Yexiang Wang creator Yi Guo creator Siqi
  Zhu writer 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 issues of dialogue state monitoring (DST).
  In this paper, we propose a brand new structure to cleverly
  exploit ontology, which consists of Slot Attention (SA) and Value Normalization (VN), referred to as SAVN.
  
  SAS: Dialogue State Tracking via Slot Attention and Slot Information Sharing Jiaying Hu author Yan Yang creator Chencai Chen writer Liang He creator 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 accountable for inferring person intentions by way of dialogue historical past.
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  Attention and Slot Information Sharing (SAS) to cut back redundant
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