| Capture, learning, and synthesis of 3D speaking styles D Cudeiro, T Bolkart, C Laidlaw, A Ranjan, MJ Black Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 363 | 2019 |
| Functional Adversarial Attacks C Laidlaw, S Feizi Advances in Neural Information Processing Systems 32, 2019 | 283* | 2019 |
| Perceptual adversarial robustness: Defense against unseen threat models C Laidlaw, S Singla, S Feizi arXiv preprint arXiv:2006.12655, 2020 | 212 | 2020 |
| The boltzmann policy distribution: Accounting for systematic suboptimality in human models C Laidlaw, A Dragan arXiv preprint arXiv:2204.10759, 2022 | 29 | 2022 |
| Distributional preference learning: Understanding and accounting for hidden context in RLHF A Siththaranjan, C Laidlaw, D Hadfield-Menell arXiv preprint arXiv:2312.08358, 2023 | 24* | 2023 |
| Playing it safe: Adversarial robustness with an abstain option C Laidlaw, S Feizi arXiv preprint arXiv:1911.11253, 2019 | 22 | 2019 |
| Bridging rl theory and practice with the effective horizon C Laidlaw, SJ Russell, A Dragan Advances in Neural Information Processing Systems 36, 58953-59007, 2023 | 20 | 2023 |
| Uncertain decisions facilitate better preference learning C Laidlaw, S Russell Advances in Neural Information Processing Systems 34, 15070-15083, 2021 | 14* | 2021 |
| Preventing reward hacking with occupancy measure regularization C Laidlaw, S Singhal, A Dragan arXiv preprint arXiv:2403.03185, 2024 | 11 | 2024 |
| Toward computationally efficient inverse reinforcement learning via reward shaping LH Cooke, H Klyne, E Zhang, C Laidlaw, M Tambe, F Doshi-Velez arXiv preprint arXiv:2312.09983, 2023 | 1 | 2023 |
| The Effective Horizon Explains Deep RL Performance in Stochastic Environments C Laidlaw, B Zhu, S Russell, A Dragan arXiv preprint arXiv:2312.08369, 2023 | 1 | 2023 |
| Scalably Solving Assistance Games C Laidlaw, E Bronstein, T Guo, D Feng, L Berglund, J Svegliato, S Russell, ... ICML 2024 Workshop on Models of Human Feedback for AI Alignment, 2024 | | 2024 |
| Scalable Oversight by Accounting for Unreliable Feedback S Singhal, C Laidlaw, A Dragan ICML 2024 Workshop on Models of Human Feedback for AI Alignment, 0 | | |
Anca D DraganAssistant Professor at UC Berkeley // Director, AI Safety and Alignment, Google DeepMind在 berkeley.edu 的电子邮件经过验证
