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Efficient Dialogue State Tracking by Masked Hierarchical Transformer

arXiv 2106.14433 ↗First posted 28 Jun 2021cs.CLcited by 0

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Abstract (arXiv)

This paper describes our approach to DSTC 9 Track 2: Cross-lingual Multi-domain Dialog State Tracking, the task goal is to build a Cross-lingual dialog state tracker with a training set in rich resource language and a testing set in low resource language. We formulate a method for joint learning of slot operation classification task and state tracking task respectively. Furthermore, we design a novel mask mechanism for fusing contextual information about dialogue, the results show the proposed model achieves excellent performance on DSTC Challenge II with a joint accuracy of 62.37% and 23.96% in MultiWOZ(en - zh) dataset and CrossWOZ(zh - en) dataset, respectively.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 18 of its 22 references that are in the map. First posted on arXiv 28 Jun 2021.

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References · 18

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  3. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  4. 2019XLNet: Generalized Autoregressive Pretraining for Language Understandingcited by 2,811
  5. 2018MultiWOZ -- A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modellingcited by 766
  6. 2019Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systemscited by 216
  7. 2019Efficient Dialogue State Tracking by Selectively Overwriting Memorycited by 76
  8. 2019Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Trackingcited by 75
  9. 2020CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Datasetcited by 66
  10. 2019SUMBT: Slot-Utterance Matching for Universal and Scalable Belief Trackingcited by 63
  11. 2019Dialog State Tracking: A Neural Reading Comprehension Approachcited by 62
  12. 2020Overview of the Ninth Dialog System Technology Challenge: DSTC9cited by 49
6 more
  1. 2019BERT-DST: Scalable End-to-End Dialogue State Tracking with Bidirectional Encoder Representations from Transformercited by 38
  2. 2018Towards Universal Dialogue State Trackingcited by 33
  3. 2020A Contextual Hierarchical Attention Network with Adaptive Objective for Dialogue State Trackingcited by 20
  4. 2020Non-Autoregressive Dialog State Trackingcited by 15
  5. 2019HyST: A Hybrid Approach for Flexible and Accurate Dialogue State Trackingcited by 14
  6. 2019Improving Dialogue State Tracking by Discerning the Relevant Contextcited by 2

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