Dual Learning for Dialogue State Tracking-Reference-Cited by-同舟云学术

Dual Learning for Dialogue State Tracking

Published:2023 Issue: Volume: Page:293-305
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
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Author:

Chen Zhi,Chen Lu,Zhao Yanbin,Zhu Su,Yu Kai

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-99-2401-1_26

Reference28 articles.

1. Budzianowski, P., et al.: MultiWOZ-a large-scale multi-domain wizard-of-OZ dataset for task-oriented dialogue modelling. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 5016–5026 (2018)

2. Cao, R., Zhu, S., Liu, C., Li, J., Yu, K.: Semantic parsing with dual learning. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 51–64 (2019)

3. Chen, Z., et al.: UniDU: towards a unified generative dialogue understanding framework. In: Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue, pp. 442–455. Association for Computational Linguistics, Edinburgh, September 2022. https://aclanthology.org/2022.sigdial-1.43

4. Chen, Z., et al.: Decoupled dialogue modeling and semantic parsing for multi-turn text-to-SQL. In: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pp. 3063–3074 (2021)

5. Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)

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