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Publication search results
found 12 matches
- 2022
- Heidy Khlaaf, Pamela Mishkin, Joshua Achiam, Gretchen Krueger, Miles Brundage:
A Hazard Analysis Framework for Code Synthesis Large Language Models. CoRR abs/2207.14157 (2022) - 2021
- Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Pondé 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, Joshua 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:
Evaluating Large Language Models Trained on Code. CoRR abs/2107.03374 (2021) - 2020
- Adam Stooke, Joshua Achiam, Pieter Abbeel:
Responsive Safety in Reinforcement Learning by PID Lagrangian Methods. ICML 2020: 9133-9143 - Adam Stooke, Joshua Achiam, Pieter Abbeel:
Responsive Safety in Reinforcement Learning by PID Lagrangian Methods. CoRR abs/2007.03964 (2020) - 2019
- Abigail Achiamma Joshua, Samanza Kishwar Parvez, Weng Ken Lee, Ee Xion Tan:
Patterns and Colors: A Simple yet Innovative Way to Solve Pattern Tracking. ACeS 2019: 33-45 - Joshua Achiam, Ethan Knight, Pieter Abbeel:
Towards Characterizing Divergence in Deep Q-Learning. CoRR abs/1903.08894 (2019) - 2018
- Alex Nichol, Joshua Achiam, John Schulman:
On First-Order Meta-Learning Algorithms. CoRR abs/1803.02999 (2018) - Joshua Achiam, Harrison Edwards, Dario Amodei, Pieter Abbeel:
Variational Option Discovery Algorithms. CoRR abs/1807.10299 (2018) - 2017
- Joshua Achiam, David Held, Aviv Tamar, Pieter Abbeel:
Constrained Policy Optimization. ICML 2017: 22-31 - Joshua Achiam, David Held, Aviv Tamar, Pieter Abbeel:
Constrained Policy Optimization. CoRR abs/1705.10528 (2017) - Joshua Achiam, Shankar Sastry:
Surprise-Based Intrinsic Motivation for Deep Reinforcement Learning. CoRR abs/1703.01732 (2017) - 2016
- Joshua Achiam:
Easy Monotonic Policy Iteration. CoRR abs/1602.09118 (2016)
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