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Current language models are considered to have sub-human capabilities at natural language tasks like question-answering or writing code.
A comparison of human and statistical language model performance using missing-word tests
M. Owens, P. O’Boyle, J. McMahon, J. Ming, and F. J. Smith · 1997
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One billion word benchmark for measuring progress in statistical language modeling
Ciprian Chelba, Tomas Mikolov, Mike Schuster, Qi Ge, T. Brants, Phillip Todd Koehn, and Tony Robinson · 2014
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Building a large annotated corpus of english: The penn treebank
Mitchell P. Marcus, Mary Ann Marcinkiewicz, and Beatrice Santorini · 2017
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Estimation of gap between current language models and human performance
Xiaoyu Shen, Youssef Oualil, Clayton Greenberg, Mittul Singh, and Dietrich Klakow · 2017
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Openwebtext corpus
A. Gokaslan and V. Cohen · 2019
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Chris olah’s views on agi safety, 2019
E Hurbinger · 2019
Cited alongside, same era.
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, T. J. Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeff 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
Cited alongside, same era.
The pile: An 800gb dataset of diverse text for language modeling
Leo Gao, Stella Biderman, Sid Black, Laurence Golding, Travis Hoppe, Charles Foster, Jason Phang, Horace He, Anish Thite, Noa Nabeshima, et al · 2020
Cited alongside, same era.
Openai’s gpt-3 language model, 2020
Steve Omohundro · 2020
Cited alongside, same era.
Better language models and their implications, 2019a
Alec Radford, Jeffrey Wu, Dario Amodei, Daniela Amodei, Jack Clark, Miles Brundage, and Ilya Sutskever
Cited in the paper.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al
Cited in the paper.
GPT-Neo: Large Scale Autoregressive Language Modeling with Mesh-Tensorflow, March 2021
Sid Black, Leo Gao, Phil Wang, Connor Leahy, and Stella Biderman · 2021
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Measuring mathematical problem solving with the math dataset
Dan Hendrycks, Collin Burns, Saurav Kadavath, Akul Arora, Steven Basart, Eric Tang, Dawn Xiaodong Song, and Jacob Steinhardt · 2021
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GPT-J-6B: A 6 Billion Parameter Autoregressive Language Model
Ben Wang and Aran Komatsuzaki · 2021
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Shared computational principles for language processing in humans and deep language models
Ariel Goldstein, Zaid Zada, Eliav Buchnik, Mariano Schain, Amy Price, Bobbi Aubrey, Samuel Nastase, Amir Feder, Dotan Emanuel, Alon Cohen, Aren Jansen, Harshvardhan Gazula, Gina Choe, Aditi Rao, Catherine Kim, Colton Casto, Lora Fanda, Werner Doyle, Daniel Friedman, and Uri Hasson · 2022
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