| 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 | 187 | 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 | 79 | 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 | 52 | 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 | 41 | 2019 |
| The MAGICAL Benchmark for Robust Imitation S Toyer, R Shah, A Critch, S Russell Advances in Neural Information Processing Systems 33, 2020 | 34 | 2020 |
| Optimal Policies Tend to Seek Power AM Turner, L Smith, R Shah, A Critch, P Tadepalli arXiv preprint arXiv:1912.01683, 2019 | 31* | 2019 |
| Active Inverse Reward Design S Mindermann, R Shah, A Gleave, D Hadfield-Menell arXiv preprint arXiv:1809.03060, 2018 | 22 | 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 | 18 | 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 | 15 | 2021 |
| 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 | 14 | 2021 |
| Benefits of Assistance over Reward Learning R Shah, P Freire, N Alex, R Freedman, D Krasheninnikov, L Chan, ... | 13 | 2020 |
| The implicit preference information in an initial state R Shah, D Krasheninnikov, J Alexander, P Abbeel, A Dragan International Conference on Learning Representations, 2019 | 11 | 2019 |
| Choice Set Misspecification in Reward Inference R Freedman, R Shah, A Dragan CEUR Workshop Proceedings, 2020 | 8 | 2020 |
| 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 | 7 | 2022 |
| 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 | 3 | 2022 |
| Automated Incrementalization through Synthesis R Shah, R Bodik Proceedings of the First Workshop on Incremental Computing, 2017 | 3 | 2017 |
| Learning What To Do by Simulating the Past D Lindner, R Shah, P Abbeel, A Dragan arXiv preprint arXiv:2104.03946, 2021 | 2 | 2021 |
| 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 | 1 | 2023 |
| Retrospective on the 2021 BASALT Competition on Learning from Human Feedback R Shah, SH Wang, C Wild, S Milani, A Kanervisto, VG Goecks, ... arXiv preprint arXiv:2204.07123, 2022 | 1 | 2022 |
| Combining reward information from multiple sources D Krasheninnikov, R Shah, H van Hoof arXiv preprint arXiv:2103.12142, 2021 | 1 | 2021 |
