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Evaluating Large Language Models Trained on Code


Jul 14, 2021
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, Alex Ray, Raul Puri, Gretchen Krueger, Michael Petrov, Heidy Khlaaf, Girish Sastry, Pamela Mishkin, Brooke Chan, Scott Gray, Nick Ryder, Mikhail Pavlov, Alethea Power, Lukasz Kaiser, Mohammad Bavarian, Clemens Winter, Philippe Tillet, Felipe Petroski Such, Dave Cummings, Matthias Plappert, Fotios Chantzis, Elizabeth Barnes, Ariel Herbert-Voss, William Hebgen Guss, Alex Nichol, Alex Paino, Nikolas Tezak, Jie Tang, Igor Babuschkin, Suchir Balaji, Shantanu Jain, William Saunders, Christopher Hesse, Andrew N. Carr, Jan Leike, Josh Achiam, Vedant Misra, Evan Morikawa, Alec Radford, Matthew Knight, Miles Brundage, Mira Murati, Katie Mayer, Peter Welinder, Bob McGrew, Dario Amodei, Sam McCandlish, Ilya Sutskever, Wojciech Zaremba

* corrected typos, added references, added authors, added acknowledgements 

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Diffusion Models Beat GANs on Image Synthesis


Jun 01, 2021
Prafulla Dhariwal, Alex Nichol

* Added compute requirements, ImageNet 256$\times$256 upsampling FID and samples, DDIM guided sampler, fixed typos 

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Improved Denoising Diffusion Probabilistic Models


Feb 18, 2021
Alex Nichol, Prafulla Dhariwal


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VQ-DRAW: A Sequential Discrete VAE


Mar 03, 2020
Alex Nichol


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On First-Order Meta-Learning Algorithms


Oct 22, 2018
Alex Nichol, Joshua Achiam, John Schulman


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Gotta Learn Fast: A New Benchmark for Generalization in RL


Apr 23, 2018
Alex Nichol, Vicki Pfau, Christopher Hesse, Oleg Klimov, John Schulman


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