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In this paper, we formulate a more realistic and difficult problem setup for the intent detection task in natural language understanding, namely Generalized Few-Shot Intent Detection (GFSID).
Unified language model pre-training for natural language understanding and generation
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Durk P Kingma, Shakir Mohamed, Danilo Jimenez Rezende, and Max Welling. 2014 · 2014
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Effective approaches to attention-based neural machine translation
Minh-Thang Luong, Hieu Pham, and Christopher D Manning. 2015 · 2015
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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton. 2016 · 2016
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Bridging nonlinearities and stochastic regularizers with gaussian error linear units
Dan Hendrycks and Kevin Gimpel. 2016 · 2016
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Matching networks for one shot learning
Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Daan Wierstra, et al. 2016 · 2016
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Google’s neural machine translation system: Bridging the gap between human and machine translation
Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, et al. 2016 · 2016
Alice Coucke, Alaa Saade, Adrien Ball, Théodore Bluche, Alexandre Caulier, David Leroy, Clément Doumouro, Thibault Gisselbrecht, Francesco Caltagirone, Thibaut Lavril, et al. 2018 · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
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Dynamic few-shot visual learning without forgetting
Spyros Gidaris and Nikos Komodakis. 2018 · 2018
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Slot-gated modeling for joint slot filling and intent prediction
Chih-Wen Goo, Guang Gao, Yun-Kai Hsu, Chih-Li Huo, Tsung-Chieh Chen, Keng-Wei Hsu, and Yun-Nung Chen. 2018 · 2018
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Few-shot and zero-shot multi-label learning for structured label spaces
Anthony Rios and Ramakanth Kavuluru. 2018 · 2018
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Meta networks
Tsendsuren Munkhdalai and Hong Yu. 2017 · 2017
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Adversarial generation of natural language
Sai Rajeswar, Sandeep Subramanian, Francis Dutil, Christopher Pal, and Aaron Courville. 2017 · 2017
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Prototypical networks for few-shot learning
Jake Snell, Kevin Swersky, and Richard Zemel. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Zero-shot learning-the good, the bad and the ugly
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Tiancheng Zhao, Ran Zhao, and Maxine Eskenazi. 2017 · 2017
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Zero-shot user intent detection via capsule neural networks
Congying Xia, Chenwei Zhang, Xiaohui Yan, Yi Chang, and Philip Yu. 2018 · 2018
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Joint slot filling and intent detection via capsule neural networks
Chenwei Zhang, Yaliang Li, Nan Du, Wei Fan, and Philip S Yu. 2018 · 2018
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Induction networks for few-shot text classification
Ruiying Geng, Binhua Li, Yongbin Li, Xiaodan Zhu, Ping Jian, and Jian Sun. 2019 · 2019
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A novel bi-directional interrelated model for joint intent detection and slot filling
E Haihong, Peiqing Niu, Zhongfu Chen, and Meina Song. 2019 · 2019
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Generalized zero-and few-shot learning via aligned variational autoencoders
Edgar Schonfeld, Sayna Ebrahimi, Samarth Sinha, Trevor Darrell, and Zeynep Akata. 2019 · 2019
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Benchmarking natural language understanding services for building conversational agents
Pawel Swietojanski Xingkun Liu, Arash Eshghi and Verena Rieser. 2019 · 2019
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Open-world learning and application to product classification
Hu Xu, Bing Liu, Lei Shu, and P Yu. 2019 · 2019
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