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WebGPT: Browser-assisted question-answering with human feedback


Dec 17, 2021
Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, Xu Jiang, Karl Cobbe, Tyna Eloundou, Gretchen Krueger, Kevin Button, Matthew Knight, Benjamin Chess, John Schulman

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* 30 pages 

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Training Verifiers to Solve Math Word Problems


Nov 18, 2021
Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, John Schulman

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Batch size-invariance for policy optimization


Oct 01, 2021
Jacob Hilton, Karl Cobbe, John Schulman

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* Submitted to ICLR 2022. 27 pages. Code is available at https://github.com/openai/ppo-ewma 

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Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark


Mar 29, 2021
Sharada Mohanty, Jyotish Poonganam, Adrien Gaidon, Andrey Kolobov, Blake Wulfe, Dipam Chakraborty, Gražvydas Šemetulskis, João Schapke, Jonas Kubilius, Jurgis Pašukonis, Linas Klimas, Matthew Hausknecht, Patrick MacAlpine, Quang Nhat Tran, Thomas Tumiel, Xiaocheng Tang, Xinwei Chen, Christopher Hesse, Jacob Hilton, William Hebgen Guss, Sahika Genc, John Schulman, Karl Cobbe

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Phasic Policy Gradient


Sep 09, 2020
Karl Cobbe, Jacob Hilton, Oleg Klimov, John Schulman

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Leveraging Procedural Generation to Benchmark Reinforcement Learning


Dec 03, 2019
Karl Cobbe, Christopher Hesse, Jacob Hilton, John Schulman

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Quantifying Generalization in Reinforcement Learning


Dec 20, 2018
Karl Cobbe, Oleg Klimov, Chris Hesse, Taehoon Kim, John Schulman

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