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ORCIDJohn Schulman
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Publications
- 2023
[c28]Leo Gao, John Schulman, Jacob Hilton:
Scaling Laws for Reward Model Overoptimization. ICML 2023: 10835-10866- [i37]Jacob Hilton, Jie Tang, John Schulman:
Scaling laws for single-agent reinforcement learning. CoRR abs/2301.13442 (2023) - 2022
- [c27]Jacob Hilton, Karl Cobbe, John Schulman:
Batch size-invariance for policy optimization. NeurIPS 2022 - [c26]Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul F. Christiano, Jan Leike, Ryan Lowe:
Training language models to follow instructions with human feedback. NeurIPS 2022 - [i35]Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul F. Christiano, Jan Leike, Ryan Lowe:
Training language models to follow instructions with human feedback. CoRR abs/2203.02155 (2022) - [i33]Leo Gao, John Schulman, Jacob Hilton:
Scaling Laws for Reward Model Overoptimization. CoRR abs/2210.10760 (2022) - 2021
- [c25]Karl Cobbe, Jacob Hilton, Oleg Klimov, John Schulman:
Phasic Policy Gradient. ICML 2021: 2020-2027 - [i31]Sharada P. Mohanty, Jyotish Poonganam, Adrien Gaidon, Andrey Kolobov, Blake Wulfe, Dipam Chakraborty, Grazvydas Semetulskis, João Schapke, Jonas Kubilius, Jurgis Pasukonis, Linas Klimas, Matthew J. 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:
Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark. CoRR abs/2103.15332 (2021) - [i29]Jacob Hilton, Karl Cobbe, John Schulman:
Batch size-invariance for policy optimization. CoRR abs/2110.00641 (2021) - [i28]Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, John Schulman:
Training Verifiers to Solve Math Word Problems. CoRR abs/2110.14168 (2021) - [i27]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:
WebGPT: Browser-assisted question-answering with human feedback. CoRR abs/2112.09332 (2021) - 2020
- [c24]Karl Cobbe, Christopher Hesse, Jacob Hilton, John Schulman:
Leveraging Procedural Generation to Benchmark Reinforcement Learning. ICML 2020: 2048-2056 - [c22]Sharada P. Mohanty, Jyotish Poonganam, Adrien Gaidon, Andrey Kolobov, Blake Wulfe, Dipam Chakraborty, Grazvydas Semetulskis, João Schapke, Jonas Kubilius, Jurgis Pasukonis, Linas Klimas, Matthew J. 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:
Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark. NeurIPS (Competition and Demos) 2020: 361-395 - [i26]Karl Cobbe, Jacob Hilton, Oleg Klimov, John Schulman:
Phasic Policy Gradient. CoRR abs/2009.04416 (2020) - 2019
- [i22]Karl Cobbe, Christopher Hesse, Jacob Hilton, John Schulman:
Leveraging Procedural Generation to Benchmark Reinforcement Learning. CoRR abs/1912.01588 (2019)
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