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Multi-task learning (MTL) significantly pre-dates the deep learning era, and it has seen a resurgence in the past few years as researchers have been applying MTL to deep learning solutions for natural language tasks.
Multi-task deep neural networks for natural language understanding
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Task2vec: Task embedding for meta-learning
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Which tasks should be learned together in multi-task learning?
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Superglue: A stickier benchmark for general-purpose language understanding systems
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Spanbert: Improving pre-training by representing and predicting spans
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Roberta: A robustly optimized bert pretraining approach
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Ellipsis and coreference resolution as question answering
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Albert: A lite bert for self-supervised learning of language representations
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Exploring the limits of transfer learning with a unified text-to-text transformer
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Not enough data? deep learning to the rescue!
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Multitask learning
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A notion of task relatedness yielding provable multiple-task learning guarantees
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Multi-task gaussian process prediction, in: NIPS, pp. 153–160
Bonilla, E.V., Chai, K.M., Williams, C., 2008 · 2008
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Mtforest: Ensemble decision trees based on multi-task learning., in: ECAI, pp. 122–126
Wang, Q., Zhang, L., Chi, M., Guo, J., 2008 · 2008
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Exploiting unrelated tasks in multi-task learning, in: International conference on artificial intelligence and statistics, pp. 951–959
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Probability models for open set recognition
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Distilling the knowledge in a neural network
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Learning to predict readability using eye-movement data from natives and learners, in: Thirty-Second AAAI Conference on Artificial Intelligence
González-Garduno, A.V., Søgaard, A., 2018 · 2018
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The natural language decathlon: Multitask learning as question answering
McCann, B., Keskar, N.S., Xiong, C., Socher, R., 2018 · 2018
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Never-ending learning
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Sentence encoders on stilts: Supplementary training on intermediate labeled-data tasks
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Improving language understanding by generative pre-training
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Luong, M.T., Le, Q.V., Sutskever, I., Vinyals, O., Kaiser, L., 2015 · 2015
Cited alongside, same era.
How transferable are neural networks in nlp applications?, in: EMNLP, pp. 479–489
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Cited alongside, same era.
Transfer learning for low-resource neural machine translation
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Cited alongside, same era.
When is multitask learning effective? semantic sequence prediction under varying data conditions, in: EACL Vol. 1, pp. 44–53
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Identifying beneficial task relations for multi-task learning in deep neural networks, in: EACL Vol. 2, pp. 164–169
Bingel, J., Søgaard, A., 2017 · 2017
Cited alongside, same era.
Reverse curriculum generation for reinforcement learning
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Cited alongside, same era.
An overview of multi-task learning in deep neural networks
Ruder, S., 2017 · 2017
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Snorkel metal: Weak supervision for multi-task learning, in: Workshop on Data Management for End-To-End Machine Learning, ACM. p. 3
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Glue: A multi-task benchmark and analysis platform for natural language understanding, in: EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, pp. 353–355
Wang, A., Singh, A., Michael, J., Hill, F., Levy, O., Bowman, S., 2018 · 2018
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Bam! born-again multi-task networks for natural language understanding, in: ACL, pp. 5931–5937
Clark, K., Luong, M.T., Khandelwal, U., Manning, C.D., Le, Q., 2019 · 2019
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Bert: Pre-training of deep bidirectional transformers for language understanding, in: NAACL-HLT Vol 1, pp. 4171–4186
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Probing what different nlp tasks teach machines about function word comprehension, in: SEM, pp. 235–249
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Continual lifelong learning with neural networks: A review
Parisi, G.I., Kemker, R., Part, J.L., Kanan, C., Wermter, S., 2019 · 2019
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Language models are unsupervised multitask learners
Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., Sutskever, I., 2019 · 2019
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Advances in Domain Adaptation Theory
Redko, I., Morvant, E., Habrard, A., Sebban, M., Bennani, Y., 2019 · 2019
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Bert and pals: Projected attention layers for efficient adaptation in multi-task learning, in: ICML, pp. 5986–5995
Stickland, A.C., Murray, I., 2019 · 2019
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