Joshua Achiam
Publications by Year
Research Areas
Reinforcement Learning in Robotics, Adversarial Robustness in Machine Learning, Advanced Bandit Algorithms Research, Software Engineering Research, Domain Adaptation and Few-Shot Learning
Most-Cited Works
- → Evaluating Large Language Models Trained on Code(2021)1,403 cited
- → On First-Order Meta-Learning Algorithms(2018)544 cited
- → Constrained Policy Optimization(2017)111 cited
- → Surprise-Based Intrinsic Motivation for Deep Reinforcement Learning(2017)100 cited
- → Variational Option Discovery Algorithms(2018)82 cited
- → Towards Characterizing Divergence in Deep Q-Learning(2019)61 cited
- → Responsive Safety in Reinforcement Learning by PID Lagrangian Methods(2020)44 cited
- → A Hazard Analysis Framework for Code Synthesis Large Language Models(2022)9 cited
- → Rule Based Rewards for Language Model Safety(2024)2 cited
- Exploration and Safety in Deep Reinforcement Learning(2021)