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Pretrained general-purpose language models can achieve state-of-the-art accuracies in various natural language processing domains by adapting to downstream tasks via zero-shot, few-shot and fine-tuning techniques.
The sausage machine: A new two-stage parsing model
Lyn Frazier and Janet D. Fodor · 1978
Earlier work this paper cites.
Language and Gender
Penelope Eckert and Sally McConnell-Ginet · 2003
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
Man is to computer programmer as woman is to homemaker? debiasing word embeddings
Tolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, and Adam Tauman Kalai · 2016
Earlier work this paper cites.
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Rafal Józefowicz, Oriol Vinyals, Mike Schuster, Noam M. Shazeer, and Yonghui Wu · 2016
Earlier work this paper cites.
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Denis Paperno, Germán Kruszewski, Angeliki Lazaridou, Ngoc Quan Pham, Raffaella Bernardi, Sandro Pezzelle, Marco Baroni, Gemma Boleda, and Raquel Fernández · 2016
Earlier work this paper cites.
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Mandar Joshi, Eunsol Choi, Daniel S. Weld, and Luke Zettlemoyer · 2017
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
Paulius Micikevicius, Sharan Narang, Jonah Alben, Gregory Diamos, Erich Elsen, David Garcia, Boris Ginsburg, Michael Houston, Oleksii Kuchaiev, Ganesh Venkatesh, et al · 2017
Earlier work this paper cites.
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Noam M. Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc V. Le, Geoffrey E. Hinton, and Jeff Dean · 2017
Earlier work this paper cites.
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Annotation artifacts in natural language inference data
Suchin Gururangan, Swabha Swayamdipta, Omer Levy, Roy Schwartz, Samuel R. Bowman, and Noah A. Smith · 2018
Earlier work this paper cites.
A simple method for commonsense reasoning
Trieu H. Trinh and Quoc V. Le · 2018
Earlier work this paper cites.
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Earlier work this paper cites.
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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
Earlier work this paper cites.
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Yanping Huang, Youlong Cheng, Ankur Bapna, Orhan Firat, Dehao Chen, Mia Chen, HyoukJoong Lee, Jiquan Ngiam, Quoc V Le, Yonghui Wu, et al · 2019
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
Black is to criminal as caucasian is to police: Detecting and removing multiclass bias in word embeddings
Thomas Manzini, Lim Yao Chong, Alan W Black, and Yulia Tsvetkov · 2019
Earlier work this paper cites.
Right for the wrong reasons: Diagnosing syntactic heuristics in natural language inference
Tom McCoy, Ellie Pavlick, and Tal Linzen · 2019
Earlier work this paper cites.
Pipedream: generalized pipeline parallelism for dnn training
Deepak Narayanan, Aaron Harlap, Amar Phanishayee, Vivek Seshadri, Nikhil R Devanur, Gregory R Ganger, Phillip B Gibbons, and Matei Zaharia · 2019
Earlier work this paper cites.
Transformers without tears: Improving the normalization of self-attention
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Earlier work this paper cites.
Asynchronous Pipeline for Processing Huge Corpora on Medium to Low Resource Infrastructures
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Wic: the word-in-context dataset for evaluating context-sensitive meaning representations
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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
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The woman worked as a babysitter: On biases in language generation
Emily Sheng, Kai-Wei Chang, Premkumar Natarajan, and Nanyun Peng · 2019
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A framework for few-shot language model evaluation, September 2021
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Gedi: Generative discriminator guided sequence generation, 2021
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Gshard: Scaling giant models with conditional computation and automatic sharding
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Learning and evaluating general linguistic intelligence
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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, 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
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M6: A chinese multimodal pretrainer
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M6-10t: A sharing-delinking paradigm for efficient multi-trillion parameter pretraining
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Unicorn on rainbow: A universal commonsense reasoning model on a new multitask benchmark
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Efficient large-scale language model training on gpu clusters using megatron-lm
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Mitigating harm in language models with conditional-likelihood filtration
Helen Ngo, Cooper Raterink, João GM Araújo, Ivan Zhang, Carol Chen, Adrien Morisot, and Nicholas Frosst · 2021
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Sentiwordnet, 2021
Christopher Potts · 2021
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Zero-infinity: Breaking the gpu memory wall for extreme scale deep learning
Samyam Rajbhandari, Olatunji Ruwase, Jeff Rasley, Shaden Smith, and Yuxiong He · 2021
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Multitask prompted training enables zero-shot task generalization
Victor Sanh, Albert Webson, Colin Raffel, Stephen H. Bach, Lintang A. Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Teven Le Scao, Arun Raja, Manan Dey, M SAIFUL BARI, Canwen Xu, Urmish Thakker, Shanya Sharma Sharma, Eliza Szczechla, Taewoon Kim, Gunjan Chhablani, Nihal V. Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault Févry, Jason Alan Fries, Ryan Teehan, Stella Biderman, Leo Gao, T. G. Owe Bers, Thomas Wolf, and Alexander M. Rush · 2021
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Self-diagnosis and self-debiasing: A proposal for reducing corpus-based bias in nlp
Timo Schick, Sahana Udupa, and Hinrich Schütze · 2021
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DeepSpeed
DeepSpeed Team · 2021
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Infobert: Improving robustness of language models from an information theoretic perspective
Boxin Wang, Shuohang Wang, Yu Cheng, Zhe Gan, R. Jia, Bo Li, and Jingjing Liu · 2021
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Towards zero-label language learning
Zirui Wang, Adams Wei Yu, Orhan Firat, and Yuan Cao · 2021
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Finetuned language models are zero-shot learners
Jason Wei, Maarten Bosma, Vincent Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, and Quoc V. Le · 2021
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Ethical and social risks of harm from language models
Laura Weidinger, John Mellor, Maribeth Rauh, Conor Griffin, Jonathan Uesato, Po-Sen Huang, Myra Cheng, Mia Glaese, Borja Balle, Atoosa Kasirzadeh, Zac Kenton, Sasha Brown, Will Hawkins, Tom Stepleton, Courtney Biles, Abeba Birhane, Julia Haas, Laura Rimell, Lisa Anne Hendricks, William Isaac, Sean Legassick, Geoffrey Irving, and Iason Gabriel · 2021
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Challenges in detoxifying language models
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Yuan 1.0: Large-scale pre-trained language model in zero-shot and few-shot learning
Shaohua Wu, Xudong Zhao, Tong Yu, Rongguo Zhang, Chong Shen, Hongli Liu, Feng Li, Hong Zhu, Jiangang Luo, Liang Xu, and Xuanwei Zhang · 2021
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Wei Zeng, Xiaozhe Ren, Teng Su, Hui Wang, Yi Liao, Zhiwei Wang, Xin Jiang, ZhenZhang Yang, Kaisheng Wang, Xiaoda Zhang, Chen Li, Ziyan Gong, Yifan Yao, Xinjing Huang, Jun Wang, Jianfeng Yu, Qilong Guo, Yue Yu, Yan Zhang, Jin Wang, Heng Tao, Dasen Yan, Zexuan Yi, Fang Peng, Fan Jiang, Han Zhang, Lingfeng Deng, Yehong Zhang, Zhengping Lin, Chao Zhang, Shaojie Zhang, Mingyue Guo, Shanzhi Gu, Gaojun Fan, Yaowei Wang, Xue Jin, Qun Liu, and Yonghong Tian · 2021
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