Joshua Achiam

According to our database, Joshua Achiam authored at least 10 papers between 2016 and 2024.

Collaborative distances:

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

2024

Rule Based Rewards for Language Model Safety.

Tong Mu, Alec Helyar, Johannes Heidecke, Joshua Achiam, Andrea Vallone, Ian Kivlichan, Molly Lin, Alex Beutel, John Schulman, Lilian Weng

CoRR, 2024

2022

A Hazard Analysis Framework for Code Synthesis Large Language Models.

Heidy Khlaaf, Pamela Mishkin, Joshua Achiam, Gretchen Krueger, Miles Brundage

CoRR, 2022

2021

Evaluating Large Language Models Trained on Code.

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

CoRR, 2021

2020

Responsive Safety in Reinforcement Learning by PID Lagrangian Methods.

Adam Stooke, Joshua Achiam, Pieter Abbeel

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

2019

Towards Characterizing Divergence in Deep Q-Learning.

Joshua Achiam, Ethan Knight, Pieter Abbeel

CoRR, 2019

2018

Variational Option Discovery Algorithms.

Joshua Achiam, Harrison Edwards, Dario Amodei, Pieter Abbeel

CoRR, 2018

On First-Order Meta-Learning Algorithms.

Alex Nichol, Joshua Achiam, John Schulman

CoRR, 2018

2017

Surprise-Based Intrinsic Motivation for Deep Reinforcement Learning.

Joshua Achiam, Shankar Sastry

CoRR, 2017

Constrained Policy Optimization.

Joshua Achiam, David Held, Aviv Tamar, Pieter Abbeel

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Easy Monotonic Policy Iteration.

Joshua Achiam

CoRR, 2016