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        <namePart type="given">Jiaying</namePart>
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    <abstract>Dialogue state tracker is responsible for inferring user intentions through dialogue history. Previous methods have difficulties in handling dialogues with long interaction context, due to the excessive information. We propose a Dialogue State Tracker with Slot Attention and Slot Information Sharing (SAS) to reduce redundant information’s interference and improve long dialogue context tracking. Specially, we first apply a Slot Attention to learn a set of slot-specific features from the original dialogue and then integrate them using a slot information sharing module. Our model yields a significantly improved performance compared to previous state-of the-art models on the MultiWOZ dataset.</abstract>
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%0 Conference Proceedings
%T SAS: Dialogue State Tracking via Slot Attention and Slot Information Sharing
%A Hu, Jiaying
%A Yang, Yan
%A Chen, Chencai
%A He, Liang
%A Yu, Zhou
%Y Jurafsky, Dan
%Y Chai, Joyce
%Y Schluter, Natalie
%Y Tetreault, Joel
%S Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F hu-etal-2020-sas
%X Dialogue state tracker is responsible for inferring user intentions through dialogue history. Previous methods have difficulties in handling dialogues with long interaction context, due to the excessive information. We propose a Dialogue State Tracker with Slot Attention and Slot Information Sharing (SAS) to reduce redundant information’s interference and improve long dialogue context tracking. Specially, we first apply a Slot Attention to learn a set of slot-specific features from the original dialogue and then integrate them using a slot information sharing module. Our model yields a significantly improved performance compared to previous state-of the-art models on the MultiWOZ dataset.
%R 10.18653/v1/2020.acl-main.567
%U https://aclanthology.org/2020.acl-main.567
%U https://doi.org/10.18653/v1/2020.acl-main.567
%P 6366-6375

Markdown (Informal)

[SAS: Dialogue State Tracking via Slot Attention and Slot Information Sharing](https://aclanthology.org/2020.acl-main.567) (Hu et al., ACL 2020)

• SAS: Dialogue State Tracking via Slot Attention and Slot Information Sharing (Hu et al., ACL 2020)

ACL

• Jiaying Hu, Yan Yang, Chencai Chen, Liang He, and Zhou Yu. 2020. SAS: Dialogue State Tracking via Slot Attention and Slot Information Sharing. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 6366–6375, Online. Association for Computational Linguistics.