On the utility of learning about humans for human-AI coordination M Carroll, R Shah, MK Ho, T Griffiths, S Seshia, P Abbeel, A Dragan Advances in Neural Information Processing Systems, 5174-5185, 2019 | 316 | 2019 |
Chlorophyll: Synthesis-aided compiler for low-power spatial architectures PM Phothilimthana, T Jelvis, R Shah, N Totla, S Chasins, R Bodik ACM SIGPLAN Notices 49 (6), 396-407, 2014 | 84 | 2014 |
Preferences Implicit in the State of the World R Shah, D Krasheninnikov, J Alexander, P Abbeel, A Dragan arXiv preprint arXiv:1902.04198, 2019 | 78* | 2019 |
On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference R Shah, N Gundotra, P Abbeel, A Dragan International Conference on Machine Learning, 5670-5679, 2019 | 63 | 2019 |
Optimal Policies Tend to Seek Power AM Turner, L Smith, R Shah, A Critch, P Tadepalli arXiv preprint arXiv:1912.01683, 2019 | 59* | 2019 |
Goal Misgeneralization: Why Correct Specifications Aren't Enough For Correct Goals R Shah, V Varma, R Kumar, M Phuong, V Krakovna, J Uesato, Z Kenton arXiv preprint arXiv:2210.01790, 2022 | 45 | 2022 |
The MAGICAL Benchmark for Robust Imitation S Toyer, R Shah, A Critch, S Russell Advances in Neural Information Processing Systems 33, 2020 | 42 | 2020 |
An Empirical Investigation of Representation Learning for Imitation X Chen, S Toyer, C Wild, S Emmons, I Fischer, KH Lee, N Alex, SH Wang, ... Thirty-fifth Conference on Neural Information Processing Systems Datasets …, 2021 | 28 | 2021 |
Active Inverse Reward Design S Mindermann, R Shah, A Gleave, D Hadfield-Menell arXiv preprint arXiv:1809.03060, 2018 | 28 | 2018 |
The MineRL BASALT Competition on Learning from Human Feedback R Shah, C Wild, SH Wang, N Alex, B Houghton, W Guss, S Mohanty, ... arXiv preprint arXiv:2107.01969, 2021 | 26 | 2021 |
Evaluating the Robustness of Collaborative Agents P Knott, M Carroll, S Devlin, K Ciosek, K Hofmann, AD Dragan, R Shah arXiv preprint arXiv:2101.05507, 2021 | 25 | 2021 |
Does Circuit Analysis Interpretability Scale? Evidence from Multiple Choice Capabilities in Chinchilla T Lieberum, M Rahtz, J Kramár, G Irving, R Shah, V Mikulik arXiv preprint arXiv:2307.09458, 2023 | 23 | 2023 |
Benefits of Assistance over Reward Learning R Shah, P Freire, N Alex, R Freedman, D Krasheninnikov, L Chan, ... | 21 | 2020 |
Choice Set Misspecification in Reward Inference R Freedman, R Shah, A Dragan CEUR Workshop Proceedings, 2020 | 16 | 2020 |
Explaining grokking through circuit efficiency V Varma, R Shah, Z Kenton, J Kramár, R Kumar arXiv preprint arXiv:2309.02390, 2023 | 15 | 2023 |
SIRL: Similarity-based Implicit Representation Learning A Bobu, Y Liu, R Shah, DS Brown, AD Dragan Proceedings of the 2023 ACM/IEEE International Conference on Human-Robot …, 2023 | 12 | 2023 |
Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition S Milani, A Kanervisto, K Ramanauskas, S Schulhoff, B Houghton, ... arXiv preprint arXiv:2303.13512, 2023 | 10 | 2023 |
Retrospective on the 2021 MineRL BASALT Competition on Learning from Human Feedback R Shah, SH Wang, C Wild, S Milani, A Kanervisto, VG Goecks, ... NeurIPS 2021 Competitions and Demonstrations Track, 259-272, 2022 | 8* | 2022 |
Learning What To Do by Simulating the Past D Lindner, R Shah, P Abbeel, A Dragan arXiv preprint arXiv:2104.03946, 2021 | 3 | 2021 |
Combining reward information from multiple sources D Krasheninnikov, R Shah, H van Hoof arXiv preprint arXiv:2103.12142, 2021 | 3 | 2021 |