Fetching the paper…
Reading the bibliography…
Conventional Intent Detection (ID) models are usually trained offline, which relies on a fixed dataset and a predefined set of intent classes.
Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J Cohen. 1989 · 1989
Earlier work this paper cites.
The ATIS Spoken Language Systems Pilot Corpus. In Speech and Natural Language: Proceedings of a Workshop
Charles T. Hemphill, John J. Godfrey, and George R. Doddington. 1990 · 1990
Earlier work this paper cites.
Continual learning in reinforcement environments
Mark B. Ring. 1995 · 1995
Earlier work this paper cites.
Lifelong Learning Algorithms
Sebastian Thrun. 1998 · 1998
Earlier work this paper cites.
Catastrophic forgetting in connectionist networks
Robert M French. 1999 · 1999
Earlier work this paper cites.
icarl: Incremental classifier and representation learning. In Proceedings of the IEEE conference on CVPR . 2001–2010
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, and Christoph H Lampert. 2017 · 2010
Earlier work this paper cites.
Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation. In Proceedings of EMNLP . 1724–1734
Kyunghyun Cho, Bart van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean. 2015 · 2015
Earlier work this paper cites.
Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al · 2017
Earlier work this paper cites.
Learning without forgetting
Zhizhong Li and Derek Hoiem. 2017 · 2017
Cited alongside, same era.
Prototypical networks for few-shot learning. In Advances in neural information processing systems . 4077–4087
Jake Snell, Kevin Swersky, and Richard Zemel. 2017 · 2017
Cited alongside, same era.
Attention is all you need. In Advances in neural information processing systems . 5998–6008
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Memory aware synapses: Learning what (not) to forget. In Proceedings of the ECCV . 139–154
Rahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny, Marcus Rohrbach, and Tinne Tuytelaars. 2018 · 2018
Cited alongside, same era.
End-to-End Incremental Learning. In Computer Vision - ECCV 2018 , Vol. 11216. 241–257
Francisco M. Castro, Manuel J. Marín-Jiménez, Nicolás Guil, Cordelia Schmid, and Karteek Alahari. 2018 · 2018
Cited alongside, same era.
An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction. In Proceedings of the 2019 EMNLP-IJCNLP . 1311–1316
Stefan Larson, Anish Mahendran, Joseph J. Peper, Christopher Clarke, Andrew Lee, Parker Hill, Jonathan K. Kummerfeld, Kevin Leach, Michael A. Laurenzano, Lingjia Tang, and Jason Mars. 2019 · 2019
Later among the works it cites.
Benchmarking Natural Language Understanding Services for Building Conversational Agents. In Increasing Naturalness and Flexibility in Spoken Dialogue Interaction - 10th IWSDS , Vol. 714. 165–183
Xingkun Liu, Arash Eshghi, Pawel Swietojanski, and Verena Rieser. 2019 · 2019
Later among the works it cites.
Sentence Embedding Alignment for Lifelong Relation Extraction. In Proceedings of the 2019 Conference of the NAACL-HLT . 796–806
Hong Wang, Wenhan Xiong, Mo Yu, Xiaoxiao Guo, Shiyu Chang, and William Yang Wang. 2019 · 2019
Later among the works it cites.
Chenwei Zhang, Yaliang Li, Nan Du, Wei Fan, and Philip Yu. 2019 · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Alice Coucke, Alaa Saade, Adrien Ball, Théodore Bluche, Alexandre Caulier, David Leroy, Clément Doumouro, Thibault Gisselbrecht, Francesco Caltagirone, Thibaut Lavril, Maël Primet, and Joseph Dureau. 2018 · 2018
Cited alongside, same era.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Proceedings of the 2019 Conference of the NAACL-HLT . 4171–4186
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
A Novel Bi-directional Interrelated Model for Joint Intent Detection and Slot Filling. In Proceedings of the 57th ACL . 5467–5471
Haihong E, Peiqing Niu, Zhongfu Chen, and Meina Song. 2019 · 2019
Cited alongside, same era.
Learning a Unified Classifier Incrementally via Rebalancing. In IEEE Conference on CVPR . 831–839
Saihui Hou, Xinyu Pan, Chen Change Loy, Zilei Wang, and Dahua Lin. 2019 · 2019
Cited alongside, same era.
Incremental Event Detection via Knowledge Consolidation Networks. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP 2020, Online, November 16-20, 2020 . 707–717
Pengfei Cao, Yubo Chen, Jun Zhao, and Taifeng Wang. 2020 · 2020
Later among the works it cites.
Continual Relation Learning via Episodic Memory Activation and Reconsolidation. In Proceedings of the 58th ACL . 6429–6440
Xu Han, Yi Dai, Tianyu Gao, Yankai Lin, Zhiyuan Liu, Peng Li, Maosong Sun, and Jie Zhou. 2020 · 2020
Later among the works it cites.
Few-Shot Class-Incremental Learning. In IEEE/CVF Conference on CVPR . 12180–12189
Xiaoyu Tao, Xiaopeng Hong, Xinyuan Chang, Songlin Dong, Xing Wei, and Yihong Gong. 2020 · 2020
Later among the works it cites.
Unknown Intent Detection Using Gaussian Mixture Model with an Application to Zero-shot Intent Classification. In Proceedings of the 58th ACL . 1050–1060
Guangfeng Yan, Lu Fan, Qimai Li, Han Liu, Xiaotong Zhang, Xiao-Ming Wu, and Albert Y. S. Lam. 2020 · 2020
Later among the works it cites.