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Currently, pre-trained models can be considered the default choice for a wide range of NLP tasks.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
Earlier work this paper cites.
Dropout: A simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2014 · 1958
Earlier work this paper cites.
Auto-Encoding Variational Bayes
Diederik P. Kingma and Max Welling. 2014 · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
Earlier work this paper cites.
Adaptive computation time for recurrent neural networks
Alex Graves. 2016 · 2016
Earlier work this paper cites.
BranchyNet: Fast inference via early exiting from deep neural networks
Surat Teerapittayanon, Bradley McDanel, and H. T. Kung. 2016 · 2016
Earlier work this paper cites.
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
Cited alongside, same era.
Glue: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amapreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman. 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.
Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Cited alongside, same era.
Albert: A lite bert for self-supervised learning of language representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2020 · 2020
Cited alongside, same era.
DeeBERT: Dynamic early exiting for accelerating BERT inference
Ji Xin, Raphael Tang, Jaejun Lee, Yaoliang Yu, and Jimmy Lin. 2020 · 2020
Later among the works it cites.
Bert loses patience: Fast and robust inference with early exit
Wangchunshu Zhou, Canwen Xu, Tao Ge, Julian McAuley, Ke Xu, and Furu Wei. 2020 · 2020
Later among the works it cites.
LeeBERT: Learned early exit for BERT with cross-level optimization
Wei Zhu. 2021 · 2020
Later among the works it cites.
Pondernet: Learning to ponder
Andrea Banino, Jan Balaguer, and Charles Blundell. 2021 · 2021
Later among the works it cites.
BERxiT: Early exiting for BERT with better fine-tuning and extension to regression
Ji Xin, Raphael Tang, Yaoliang Yu, and Jimmy Lin. 2021 · 2021
Later among the works it cites.
A global past-future early exit method for accelerating inference of pre-trained language models
Kaiyuan Liao, Yi Zhang, Xuancheng Ren, Qi Su, Xu Sun, and Bin He. 2021 · 2023
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Fastbert: a self-distilling BERT with adaptive inference time
Weijie Liu, Peng Zhou, Zhiruo Wang, Zhe Zhao, Haotang Deng, and Qi Ju. 2020 · 2020
Cited alongside, same era.
Closest in time.