Karl Cobbe

According to our database, Karl Cobbe authored at least 8 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Let's Verify Step by Step.

Hunter Lightman, Vineet Kosaraju, Yura Burda, Harrison Edwards, Bowen Baker, Teddy Lee, Jan Leike, John Schulman, Ilya Sutskever, Karl Cobbe

CoRR, 2023

2022

Batch size-invariance for policy optimization.

Jacob Hilton, Karl Cobbe, John Schulman

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

WebGPT: Browser-assisted question-answering with human feedback.

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

CoRR, 2021

Training Verifiers to Solve Math Word Problems.

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

CoRR, 2021

Phasic Policy Gradient.

Karl Cobbe, Jacob Hilton, Oleg Klimov, John Schulman

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

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

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

Proceedings of the NeurIPS 2020 Competition and Demonstration Track, 2020

Leveraging Procedural Generation to Benchmark Reinforcement Learning.

Karl Cobbe, Christopher Hesse, Jacob Hilton, John Schulman

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Quantifying Generalization in Reinforcement Learning.

Karl Cobbe, Oleg Klimov, Christopher Hesse, Taehoon Kim, John Schulman

Proceedings of the 36th International Conference on Machine Learning, 2019