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The success of Pre-Trained Models (PTMs) has reshaped the development of Natural Language Processing (NLP).
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.
Distilbert, a distilled version of BERT: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019 · 1910
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BERT is not a knowledge base (yet): Factual knowledge vs. name-based reasoning in unsupervised QA
Nina Pörner, Ulli Waltinger, and Hinrich Schütze. 2019 · 1911
Earlier work this paper cites.
Pre-trained models for natural language processing: A survey
Xipeng Qiu, Tianxiang Sun, Yige Xu, Yunfan Shao, Ning Dai, and Xuanjing Huang. 2020 · 2003
Earlier work this paper cites.
Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification
John Blitzer, Mark Dredze, and Fernando Pereira. 2007 · 2007
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Convolutional neural networks for sentence classification
Yoon Kim. 2014 · 2014
Earlier work this paper cites.
Distilling the knowledge in a neural network
Geoffrey E. Hinton, Oriol Vinyals, and Jeffrey Dean. 2015 · 2015
Earlier work this paper cites.
Alime chat: A sequence to sequence and rerank based chatbot engine
Minghui Qiu, Feng-Lin Li, Siyu Wang, Xing Gao, Yan Chen, Weipeng Zhao, Haiqing Chen, Jun Huang, and Wei Chu. 2017 · 2017
Earlier work this paper cites.
A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel R. Bowman. 2018 · 2018
Earlier work this paper cites.
Transformer-xl: Attentive language models beyond a fixed-length context
Zihang Dai, Zhilin Yang, Yiming Yang, Jaime G. Carbonell, Quoc Viet Le, and Ruslan Salakhutdinov. 2019 · 2019
Earlier work this paper cites.
BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Language models as knowledge bases?
Fabio Petroni, Tim Rocktäschel, Sebastian Riedel, Patrick S. H. Lewis, Anton Bakhtin, Yuxiang Wu, and Alexander H. Miller. 2019 · 2019
Cited alongside, same era.
Patient knowledge distillation for BERT model compression
Siqi Sun, Yu Cheng, Zhe Gan, and Jingjing Liu. 2019 · 2019
Cited alongside, same era.
GLUE: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman. 2019 · 2019
Cited alongside, same era.
Xlnet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan Salakhutdinov, and Quoc V. Le. 2019 · 2019
Cited alongside, same era.
ERNIE: enhanced language representation with informative entities
Zhengyan Zhang, Xu Han, Zhiyuan Liu, Xin Jiang, Maosong Sun, and Qun Liu. 2019 · 2019
Cited alongside, same era.
Language models are few-shot learners
CLUE: A chinese language understanding evaluation benchmark
Liang Xu, Hai Hu, Xuanwei Zhang, Lu Li, Chenjie Cao, Yudong Li, Yechen Xu, Kai Sun, Dian Yu, Cong Yu, Yin Tian, Qianqian Dong, Weitang Liu, Bo Shi, Yiming Cui, Junyi Li, Jun Zeng, Rongzhao Wang, Weijian Xie, Yanting Li, Yina Patterson, Zuoyu Tian, Yiwen Zhang, He Zhou, Shaoweihua Liu, Zhe Zhao, Qipeng Zhao, Cong Yue, Xinrui Zhang, Zhengliang Yang, Kyle Richardson, and Zhenzhong Lan. 2020 · 2020
Later among the works it cites.
Making pre-trained language models better few-shot learners
Tianyu Gao, Adam Fisch, and Danqi Chen. 2021 · 2021
Later among the works it cites.
Meta-kd: A meta knowledge distillation framework for language model compression across domains
Haojie Pan, Chengyu Wang, Minghui Qiu, Yichang Zhang, Yaliang Li, and Jun Huang. 2021 · 2021
Later among the works it cites.
Easytransfer: A simple and scalable deep transfer learning platform for NLP applications
Minghui Qiu, Peng Li, Chengyu Wang, Haojie Pan, Ang Wang, Cen Chen, Xianyan Jia, Yaliang Li, Jun Huang, Deng Cai, and Wei Lin. 2021 · 2021
Later among the works it cites.
Exploiting cloze-questions for few-shot text classification and natural language inference
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Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2020
Cited alongside, same era.
Revisiting pre-trained models for chinese natural language processing
Yiming Cui, Wanxiang Che, Ting Liu, Bing Qin, Shijin Wang, and Guoping Hu. 2020 · 2020
Cited alongside, same era.
K-BERT: enabling language representation with knowledge graph
Weijie Liu, Peng Zhou, Zhe Zhao, Zhiruo Wang, Qi Ju, Haotang Deng, and Ping Wang. 2020 · 2020
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
Cited alongside, same era.
Colake: Contextualized language and knowledge embedding
Tianxiang Sun, Yunfan Shao, Xipeng Qiu, Qipeng Guo, Yaru Hu, Xuanjing Huang, and Zheng Zhang. 2020 · 2020
Cited alongside, same era.
Tinybert: Distilling BERT for natural language understanding
Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, and Qun Liu. 2020a
Cited in the paper.
Tinybert: Distilling BERT for natural language understanding
Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, and Qun Liu. 2020b
Cited in the paper.
Timo Schick and Hinrich Schütze. 2021 · 2021
Later among the works it cites.
When few-shot learning meets large-scale knowledge-enhanced pre-training: Alibaba at fewclue
Ziyun Xu, Chengyu Wang, Peng Li, Yang Li, Ming Wang, Boyu Hou, Minghui Qiu, Chengguang Tang, and Jun Huang. 2021 · 2021
Later among the works it cites.
Drop redundant, shrink irrelevant: Selective knowledge injection for language pretraining
Ningyu Zhang, Shumin Deng, Xu Cheng, Xi Chen, Yichi Zhang, Wei Zhang, and Huajun Chen. 2021 · 2021
Later among the works it cites.
Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, and Noah Fiedel. 2022 · 2022
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Making pre-trained language models end-to-end few-shot learners with contrastive prompt tuning
Ziyun Xu, Chengyu Wang, Minghui Qiu, Fuli Luo, Runxin Xu, Songfang Huang, and Jun Huang. 2022 · 2022
Closest in time.
DKPLM: decomposable knowledge-enhanced pre-trained language model for natural language understanding
Taolin Zhang, Chengyu Wang, Nan Hu, Minghui Qiu, Chengguang Tang, Xiaofeng He, and Jun Huang. 2022 · 2022
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