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Few-shot learning arises in important practical scenarios, such as when a natural language understanding system needs to learn new semantic labels for an emerging, resource-scarce domain.
Meta-dataset: A dataset of datasets for learning to learn from few examples
Eleni Triantafillou, Tyler Zhu, Vincent Dumoulin, Pascal Lamblin, Kelvin Xu, Ross Goroshin, Carles Gelada, Kevin Swersky, Pierre-Antoine Manzagol, and Hugo Larochelle. 2019 · 1903
Earlier work this paper cites.
Real-time inference in multi-sentence tasks with deep pretrained transformers
Samuel Humeau, Kurt Shuster, Marie-Anne Lachaux, and Jason Weston. 2019 · 1905
Earlier work this paper cites.
The viterbi algorithm
G. D. Forney. 1973 · 1973
Earlier work this paper cites.
Distance metric learning for large margin nearest neighbor classification
Kilian Q Weinberger, John Blitzer, and Lawrence Saul. 2006 · 2006
Earlier work this paper cites.
The dit++ taxonomy for functional dialogue markup
Harry Bunt. 2009 · 2009
Earlier work this paper cites.
Bidirectional LSTM-CRF models for sequence tagging
Zhiheng Huang, Wei Xu, and Kai Yu. 2015 · 2015
Earlier work this paper cites.
Siamese neural networks for one-shot image recognition
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Earlier work this paper cites.
Facenet: A unified embedding for face recognition and clustering
Florian Schroff, Dmitry Kalenichenko, and James Philbin. 2015 · 2015
Earlier work this paper cites.
Matching networks for one shot learning
Oriol Vinyals, Charles Blundell, Timothy Lillicrap, koray kavukcuoglu, and Daan Wierstra. 2016 · 2016
Earlier work this paper cites.
Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine. 2017 · 2017
Earlier work this paper cites.
Prototypical networks for few-shot learning
Jake Snell, Kevin Swersky, and Richard Zemel. 2017 · 2017
Earlier work this paper cites.
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
Earlier work this paper cites.
A simple neural attentive meta-learner
Nikhil Mishra, Mostafa Rohaninejad, Xi Chen, and Pieter Abbeel. 2018 · 2018
Earlier work this paper cites.
Deep contextualized word representations
Matthew Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
Earlier work this paper cites.
Diverse few-shot text classification with multiple metrics
Mo Yu, Xiaoxiao Guo, Jinfeng Yi, Shiyu Chang, Saloni Potdar, Yu Cheng, Gerald Tesauro, Haoyu Wang, and Bowen Zhou. 2018 · 2018
Cited alongside, same era.
Guiding neural machine translation with retrieved translation pieces
Jingyi Zhang, Masao Utiyama, Eiichro Sumita, Graham Neubig, and Satoshi Nakamura. 2018 · 2018
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Few-shot classification in named entity recognition task
Alexander Fritzler, Varvara Logacheva, and Maksim Kretov. 2019 · 2019
Cited alongside, same era.
Induction networks for few-shot text classification
Ruiying Geng, Binhua Li, Yongbin Li, Xiaodan Zhu, Ping Jian, and Jian Sun. 2019 · 2019
Cited alongside, same era.
Learning dense representations for entity retrieval
Gunrock: A social bot for complex and engaging long conversations
Dian Yu, Michelle Cohn, Yi Mang Yang, Chun Yen Chen, Weiming Wen, Jiaping Zhang, Mingyang Zhou, Kevin Jesse, Austin Chau, Antara Bhowmick, Shreenath Iyer, Giritheja Sreenivasulu, Sam Davidson, Ashwin Bhandare, and Zhou Yu. 2019 · 2019
Later among the works it cites.
Midas: A dialog act annotation scheme for open domain human machine spoken conversations
Dian Yu and Zhou Yu. 2019 · 2019
Later among the works it cites.
Realm: Retrieval-augmented language model pre-training
Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Ming-Wei Chang. 2020 · 2020
Later among the works it cites.
Few-shot slot tagging with collapsed dependency transfer and label-enhanced task-adaptive projection network
Yutai Hou, Wanxiang Che, Yongkui Lai, Zhihan Zhou, Yijia Liu, Han Liu, and Ting Liu. 2020 · 2020
Later among the works it cites.
SpanBERT: Improving pre-training by representing and predicting spans
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Daniel Gillick, Sayali Kulkarni, Larry Lansing, Alessandro Presta, Jason Baldridge, Eugene Ie, and Diego Garcia-Olano. 2019 · 2019
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An evaluation dataset for intent classification and out-of-scope prediction
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
Cited alongside, same era.
Text generation with exemplar-based adaptive decoding
Hao Peng, Ankur Parikh, Manaal Faruqui, Bhuwan Dhingra, and Dipanjan Das. 2019 · 2019
Cited alongside, same era.
Hierarchical attention prototypical networks for few-shot text classification
Shengli Sun, Qingfeng Sun, Kevin Zhou, and Tengchao Lv. 2019 · 2019
Cited alongside, same era.
Simpleshot: Revisiting nearest-neighbor classification for few-shot learning
Yan Wang, Wei-Lun Chao, Kilian Q. Weinberger, and Laurens van der Maaten. 2019 · 2019
Cited alongside, same era.
Label-agnostic sequence labeling by copying nearest neighbors
Sam Wiseman and Karl Stratos. 2019 · 2019
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Transferable multi-domain state generator for task-oriented dialogue systems
Chien-Sheng Wu, Andrea Madotto, Ehsan Hosseini-Asl, Caiming Xiong, Richard Socher, and Pascale Fung. 2019 · 2019
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Mandar Joshi, Danqi Chen, Yinhan Liu, Daniel S. Weld, Luke Zettlemoyer, and Omer Levy. 2020 · 2020
Later among the works it cites.
Generalization through memorization: Nearest neighbor language models
Urvashi Khandelwal, Omer Levy, Dan Jurafsky, Luke Zettlemoyer, and Mike Lewis. 2020 · 2020
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Learning to classify intents and slot labels given a handful of examples
Jason Krone, Yi Zhang, and Mona Diab. 2020 · 2020
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Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandara Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen tau Yih, Tim Rocktäschel, Sebastian Riedel, and Douwe Kiela. 2020 · 2020
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Gunrock 2.0: A User Adaptive Social Conversational System
Kai-Hui Liang, Austin Chau, Yu Li, Xueyuan Lu, Dian Yu, Mingyang Zhou, Ishan Jain, Sam Davidson, Josh Arnold, Minh Nguyen, and Zhou Yu. 2020 · 2020
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Intention detection based on siamese neural network with triplet loss
F. Ren and S. Xue. 2020 · 2020
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Revisiting training strategies and generalization performance in deep metric learning
Karsten Roth, Timo Milbich, Samarth Sinha, Prateek Gupta, Björn Ommer, and Joseph Paul Cohen. 2020 · 2020
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A cross-task analysis of text span representations
Shubham Toshniwal, Haoyue Shi, Bowen Shi, Lingyu Gao, Karen Livescu, and Kevin Gimpel. 2020 · 2020
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Simple and effective few-shot named entity recognition with structured nearest neighbor learning
Yi Yang and Arzoo Katiyar. 2020 · 2020
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Example-based named entity recognition
Morteza Ziyadi, Yuting Sun, Abhishek Goswami, Jade Huang, and Weizhu Chen. 2020 · 2020
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