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Slot Attention with Value Normalization for Multi-Domain Dialogue State
Tracking Yexiang Wang creator Yi Guo creator Siqi Zhu creator 2020-nov textual content Proceedings of the 2020 Conference on Empirical Methods in Natural Language
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of dialogue state monitoring (DST). In this paper, we suggest a new structure to cleverly exploit ontology, which
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SAS: Dialogue State Tracking via Slot Attention and Slot Information Sharing Jiaying Hu creator Yan Yang author Chencai
Chen author Liang He writer Zhou Yu author
2020-jul text Proceedings of the 58th Annual Meeting of
the Association for Computational Linguistics Association for Computational Linguistics Online convention publication Dialogue state tracker is liable for inferring person intentions via dialogue historical past.
We suggest a Dialogue State Tracker with Slot Attention and Slot Information Sharing (SAS) to cut back redundant information’s interference and enhance long dialogue context tracking.

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