陈俊帆
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陈俊帆
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论文
Parallel Interactive Networks for Multi-Domain Dialogue State Generation
发布时间：2025-10-22点击次数：
发表刊物：
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), CCF-A
摘要：
The dependencies between system and user utterances in the same turn and across different turns are not fully considered in existing multi-domain dialogue state tracking (MDST) models. In this study, we argue that the incorporation of these dependencies is crucial for the design of MDST and propose Parallel Interactive Networks (PIN) to model these dependencies. Specifically, we integrate an interactive encoder to jointly model the in-turn dependencies and cross-turn dependencies. The slot-level context is introduced to extract more expressive features for different slots. And a distributed copy mechanism is utilized to selectively copy words from historical system utterances or historical user utterances. Empirical studies demonstrated the superiority of the proposed PIN model.
合写作者：
陈俊帆,张日崇, Yongyi Mao, Jie Xu
论文类型：
国际学术会议
页面范围：
1921--1931
是否译文：
否
发表时间：
2020-01-01