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Transformers have revolutionized almost all natural language processing (NLP) tasks but suffer from memory and computational complexity that scales quadratically with sequence length.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
Earlier work this paper cites.
Boolq: Exploring the surprising difficulty of natural yes/no questions
Christopher Clark, Kenton Lee, Ming-Wei Chang, Tom Kwiatkowski, Michael Collins, and Kristina Toutanova. 2019 · 1905
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
The vanishing gradient problem during learning recurrent neural nets and problem solutions
Sepp Hochreiter. 1998 · 1998
Earlier work this paper cites.
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Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei. 2020 · 2001
Earlier work this paper cites.
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Nikita Kitaev, L. Kaiser, and Anselm Levskaya. 2020 · 2001
Earlier work this paper cites.
Longformer: The long-document transformer
Iz Beltagy, Matthew E. Peters, and Arman Cohan. 2020 · 2004
Earlier work this paper cites.
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Tom Henighan, Jared Kaplan, Mor Katz, Mark Chen, Christopher Hesse, Jacob Jackson, Heewoo Jun, Tom B Brown, Prafulla Dhariwal, Scott Gray, et al. 2020 · 2010
Earlier work this paper cites.
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Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E. Hinton. 2016 · 2016
Earlier work this paper cites.
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Earlier work this paper cites.
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Phong Le and Willem Zuidema. 2016 · 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 Fernandez. 2016 · 2016
Earlier work this paper cites.
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Earlier work this paper cites.
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Matt Gardner Johannes Welbl Nelson F. Liu. 2017 · 2017
Earlier work this paper cites.
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Earlier work this paper cites.
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Tao Lei, Yu Zhang, Sida I. Wang, Hui Dai, and Yoav Artzi. 2018 · 2018
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Köpf, Edward Yang, Zach DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019 · 2019
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Earlier work this paper cites.
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Six attributes of unhealthy conversations
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What language model to train if you have one million gpu hours?
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Introducing chatgpt
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Self-attention does not need o ( n 2 ) o(n^{2}) memory
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Bloom: A 176b-parameter open-access multilingual language model
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