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Zero/few-shot transfer to unseen services is a critical challenge in task-oriented dialogue research.
Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems
Wu, C.-S.; Madotto, A.; Hosseini-Asl, E.; Xiong, C.; Socher, R.; and Fung, P. 2019 · 1905
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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Raffel, C.; Shazeer, N.; Roberts, A.; Lee, K.; Narang, S.; Matena, M.; Zhou, Y.; Li, W.; and Liu, P. J. 2020 · 1910
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Improving robustness of task oriented dialog systems
Einolghozati, A.; Gupta, S.; Mohit, M.; and Shah, R. 2019 · 1911
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Ma, Y.; Zeng, Z.; Zhu, D.; Li, X.; Yang, Y.; Yao, X.; Zhou, K.; and Shen, J. 2019 · 1912
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Schema-guided dialogue state tracking task at DSTC8
Rastogi, A.; Zang, X.; Sunkara, S.; Gupta, R.; and Khaitan, P. 2020a · 2002
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Fine-tuning bert for schema-guided zero-shot dialogue state tracking
Ruan, Y.-P.; Ling, Z.-H.; Gu, J.-C.; and Liu, Q. 2020 · 2002
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The many faces of robustness: A critical analysis of out-of-distribution generalization
Hendrycks, D.; Basart, S.; Mu, N.; Kadavath, S.; Wang, F.; Dorundo, E.; Desai, R.; Zhu, T.; Parajuli, S.; Guo, M.; et al. 2020 · 2006
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The sppd system for schema guided dialogue state tracking challenge
Li, M.; Xiong, H.; and Cao, Y. 2020 · 2006
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A Fast and Robust BERT-based Dialogue State Tracker for Schema-Guided Dialogue Dataset
Noroozi, V.; Zhang, Y.; Bakhturina, E.; and Kornuta, T. 2020 · 2008
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Star: A schema-guided dialog dataset for transfer learning
Mosig, J. E.; Mehri, S.; and Kober, T. 2020 · 2010
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Robustness Testing of Language Understanding in Task-Oriented Dialog
Liu, J.; Takanobu, R.; Wen, J.; Wan, D.; Li, H.; Nie, W.; Li, C.; Peng, W.; and Huang, M. 2020 · 2012
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Word-based dialog state tracking with recurrent neural networks
Henderson, M.; Thomson, B.; and Young, S. 2014 · 2014
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Adam: A method for stochastic optimization
Kingma, D. P.; and Ba, J. 2014 · 2014
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Improving Neural Machine Translation Models with Monolingual Data
Sennrich, R.; Haddow, B.; and Birch, A. 2016 · 2016
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Towards zero-shot frame semantic parsing for domain scaling
Bapna, A.; Tur, G.; Hakkani-Tur, D.; and Heck, L. 2017 · 2017
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In-datacenter performance analysis of a tensor processing unit
Jouppi, N. P.; Young, C.; Patil, N.; Patterson, D.; Agrawal, G.; Bajwa, R.; Bates, S.; Bhatia, S.; Boden, N.; Borchers, A.; et al. 2017 · 2017
Cited alongside, same era.
Neural Belief Tracker: Data-Driven Dialogue State Tracking
Mrkšić, N.; Séaghdha, D. Ó.; Wen, T.-H.; Thomson, B.; and Young, S. 2017 · 2017
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Synthetic and Natural Noise Both Break Neural Machine Translation
Belinkov, Y.; and Bisk, Y. 2018 · 2018
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SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization
Jiang, H.; He, P.; Chen, W.; Liu, X.; Gao, J.; and Zhao, T. 2020 · 2020
Later among the works it cites.
Ma-dst: Multi-attention-based scalable dialog state tracking
Kumar, A.; Ku, P.; Goyal, A.; Metallinou, A.; and Hakkani-Tur, D. 2020 · 2020
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A Comparative Study on Schema-Guided Dialogue State Tracking
Cao, J.; and Zhang, Y. 2021 · 2021
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Robustness Gym: Unifying the NLP Evaluation Landscape
Goel, K.; Rajani, N.; Vig, J.; Taschdjian, Z.; Bansal, M.; and Ré, C. 2021 · 2021
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Dialogue State Tracking with a Language Model using Schema-Driven Prompting
Lee, C.-H.; Cheng, H.; and Ostendorf, M. 2021 · 2021
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Budzianowski, P.; Wen, T.-H.; Tseng, B.-H.; Casanueva, I.; Ultes, S.; Ramadan, O.; and Gašić, M. 2018 · 2018
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Sequence-to-Sequence Data Augmentation for Dialogue Language Understanding
Hou, Y.; Liu, Y.; Che, W.; and Liu, T. 2018 · 2018
Cited alongside, same era.
Evaluating and enhancing the robustness of dialogue systems: A case study on a negotiation agent
Cheng, M.; Wei, W.; and Hsieh, C.-J. 2019 · 2019
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Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human Attack
Dinan, E.; Humeau, S.; Chintagunta, B.; and Weston, J. 2019 · 2019
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Pytorch: An imperative style, high-performance deep learning library
Paszke, A.; Gross, S.; Massa, F.; Lerer, A.; Bradbury, J.; Chanan, G.; Killeen, T.; Lin, Z.; Gimelshein, N.; Antiga, L.; et al. 2019 · 2019
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Robust Zero-Shot Cross-Domain Slot Filling with Example Values
Shah, D.; Gupta, R.; Fayazi, A.; and Hakkani-Tur, D. 2019 · 2019
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Data augmentation for spoken language understanding via joint variational generation
Yoo, K. M.; Shin, Y.; and Lee, S.-g. 2019 · 2019
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Zero-shot Generalization in Dialog State Tracking through Generative Question Answering
Li, S.; Cao, J.; Sridhar, M.; Zhu, H.; Li, S.-W.; Hamza, W.; and McAuley, J. 2021 · 2021
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Leveraging Slot Descriptions for Zero-Shot Cross-Domain Dialogue StateTracking
Lin, Z.; Liu, B.; Moon, S.; Crook, P. A.; Zhou, Z.; Wang, Z.; Yu, Z.; Madotto, A.; Cho, E.; and Subba, R. 2021 · 2021
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Schema-Guided Paradigm for Zero-Shot Dialog
Mehri, S.; and Eskenazi, M. 2021 · 2021
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Finetuned Language Models Are Zero-Shot Learners
Wei, J.; Bosma, M.; Zhao, V. Y.; Guu, K.; Yu, A. W.; Lester, B.; Du, N.; Dai, A. M.; and Le, Q. V. 2021 · 2021
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SGD-QA: Fast Schema-Guided Dialogue State Tracking for Unseen Services
Zhang, Y.; Noroozi, V.; Bakhturina, E.; and Ginsburg, B. 2021 · 2021
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spaCy: Industrial-strength Natural Language Processing in Python
Honnibal, M.; Montani, I.; Van Landeghem, S.; and Boyd, A. 2020 · 2022
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Adversarial Examples for Evaluating Reading Comprehension Systems
Jia, R.; and Liang, P. 2017 · 2031
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