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Existing approaches to lifelong language learning rely on plenty of labeled data for learning a new task, which is hard to obtain in most real scenarios.
Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J Cohen · 1989
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Lifelong robot learning
Sebastian Thrun and Tom M. Mitchell · 1995
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Introduction to the conll-2003 shared task: Language-independent named entity recognition
Erik F Sang and Fien De Meulder · 2003
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Ontonotes: the 90% solution
Eduard Hovy, Mitch Marcus, Martha Palmer, Lance Ramshaw, and Ralph Weischedel · 2006
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Making pre-trained language models better few-shot learners
Tianyu Gao, Adam Fisch, and Danqi Chen · 2012
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A sick cure for the evaluation of compositional distributional semantic models
Marco Marelli, Stefano Menini, Marco Baroni, Luisa Bentivogli, Raffaella Bernardi, Roberto Zamparelli, et al · 2014
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Net2net: Accelerating learning via knowledge transfer
Tianqi Chen, Ian Goodfellow, and Jonathon Shlens · 2015
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Dbpedia–a large-scale, multilingual knowledge base extracted from wikipedia
Jens Lehmann, Robert Isele, Max Jakob, Anja Jentzsch, Dimitris Kontokostas, Pablo N Mendes, Sebastian Hellmann, Mohamed Morsey, Patrick Van Kleef, Sören Auer, et al · 2015
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Image-based recommendations on styles and substitutes
Julian McAuley, Christopher Targett, Qinfeng Shi, and Anton Van Den Hengel · 2015
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Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun · 2015
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Ask me anything: Dynamic memory networks for natural language processing
Ankit Kumar, Ozan Irsoy, Peter Ondruska, Mohit Iyyer, James Bradbury, Ishaan Gulrajani, Victor Zhong, Romain Paulus, and Richard Socher · 2016
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Abstractive text summarization using sequence-to-sequence rnns and beyond
Ramesh Nallapati, Bowen Zhou, Caglar Gulcehre, Bing Xiang, et al · 2016
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Andrei A Rusu, Neil C Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, and Raia Hadsell · 2016
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Learning to learn without gradient descent by gradient descent
Yutian Chen, Matthew W. Hoffman, Sergio Gómez Colmenarejo, Misha Denil, Timothy P. Lillicrap, Matt Botvinick, and Nando de Freitas · 2017
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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
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Learning without forgetting
Zhizhong Li and Derek Hoiem · 2017
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Gradient episodic memory for continual learning
David Lopez-Paz and Marc’Aurelio Ranzato · 2017
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Few-shot learning through an information retrieval lens, 2017
Eleni Triantafillou, Richard Zemel, and Raquel Urtasun · 2017
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A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel R Bowman · 2017
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Lifelong learning with dynamically expandable networks
Jaehong Yoon, Eunho Yang, Jeongtae Lee, and Sung Ju Hwang · 2017
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Memory aware synapses: Learning what (not) to forget
Rahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny, Marcus Rohrbach, and Tinne Tuytelaars · 2018
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One-shot unsupervised cross domain translation
Sagie Benaim and Lior Wolf · 2018
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Efficient lifelong learning with a-gem
Arslan Chaudhry, Marc’Aurelio Ranzato, Marcus Rohrbach, and Mohamed Elhoseiny · 2018
Lamol: Language modeling for lifelong language learning
Fan-Keng Sun, Cheng-Hao Ho, and Hung-Yi Lee · 2019
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Sentence embedding alignment for lifelong relation extraction
Hong Wang, Wenhan Xiong, Mo Yu, Xiaoxiao Guo, Shiyu Chang, and William Yang Wang · 2019
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Continual lifelong learning in natural language processing: A survey
Magdalena Biesialska, Katarzyna Biesialska, and Marta R Costa-jussà · 2020
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Language models are few-shot learners
Tom B Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Universal language model fine-tuning for text classification
Jeremy Howard and Sebastian Ruder · 2018
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Few-shot charge prediction with discriminative legal attributes
Zikun Hu, Xiang Li, Cunchao Tu, Zhiyuan Liu, and Maosong Sun · 2018
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Scitail: A textual entailment dataset from science question answering
Tushar Khot, Ashish Sabharwal, and Peter Clark · 2018
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Wikihow: A large scale text summarization dataset
Mahnaz Koupaee and William Yang Wang · 2018
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Piggyback: Adapting a single network to multiple tasks by learning to mask weights
Arun Mallya, Dillon Davis, and Svetlana Lazebnik · 2018
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The natural language decathlon: Multitask learning as question answering
Bryan McCann, Nitish Shirish Keskar, Caiming Xiong, and Richard Socher · 2018
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Shashi Narayan, Shay B Cohen, and Mirella Lapata · 2018
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Yung-Sung Chuang, Shang-Yu Su, and Yun-Nung Chen · 2020
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Exploiting cloze questions for few shot text classification and natural language inference
Timo Schick and Hinrich Schütze · 2020
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Autoprompt: Eliciting knowledge from language models with automatically generated prompts
Taylor Shin, Yasaman Razeghi, Robert L Logan IV, Eric Wallace, and Sameer Singh · 2020
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Distill and replay for continual language learning
Jingyuan Sun, Shaonan Wang, Jiajun Zhang, and Chengqing Zong · 2020
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Pada: A prompt-based autoregressive approach for adaptation to unseen domains
Eyal Ben-David, Nadav Oved, and Roi Reichart · 2021
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Prompt-learning for fine-grained entity typing
Ning Ding, Yulin Chen, Xu Han, Guangwei Xu, Pengjun Xie, Hai-Tao Zheng, Zhiyuan Liu, Juanzi Li, and Hong-Gee Kim · 2021
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Ptr: Prompt tuning with rules for text classification
Xu Han, Weilin Zhao, Ning Ding, Zhiyuan Liu, and Maosong Sun · 2021
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Rational lamol: A rationale-based lifelong learning framework
Kasidis Kanwatchara, Thanapapas Horsuwan, Piyawat Lertvittayakumjorn, Boonserm Kijsirikul, and Peerapon Vateekul · 2021
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How many data points is a prompt worth?
Teven Le Scao and Alexander M Rush · 2021
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The power of scale for parameter-efficient prompt tuning
Brian Lester, Rami Al-Rfou, and Noah Constant · 2021
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Prefix-tuning: Optimizing continuous prompts for generation
Xiang Lisa Li and Percy Liang · 2021
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AdapterFusion: Non-destructive task composition for transfer learning
Jonas Pfeiffer, Aishwarya Kamath, Andreas Rücklé, Kyunghyun Cho, and Iryna Gurevych · 2021
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Improving and simplifying pattern exploiting training
Derek Tam, Rakesh R Menon, Mohit Bansal, Shashank Srivastava, and Colin Raffel · 2021
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Meta-tuning language models to answer prompts better
Ruiqi Zhong, Kristy Lee, Zheng Zhang, and Dan Klein · 2021
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