| Pretraining Representations for Data-Efficient Reinforcement Learning M Schwarzer, N Rajkumar, M Noukhovitch, A Anand, L Charlin, D Hjelm, ... NeurIPS, 2021 | 133 | 2021 |
| In search of robust measures of generalization GK Dziugaite, A Drouin, B Neal, N Rajkumar, E Caballero, L Wang, ... NeurIPS, 2020 | 95 | 2020 |
| Evaluating the text-to-sql capabilities of large language models N Rajkumar, R Li, D Bahdanau arXiv preprint arXiv:2204.00498, 2022 | 93 | 2022 |
| Harms from increasingly agentic algorithmic systems A Chan, R Salganik, A Markelius, C Pang, N Rajkumar, D Krasheninnikov, ... Proceedings of the 2023 ACM Conference on Fairness, Accountability, and …, 2023 | 58* | 2023 |
| Metadata archaeology: Unearthing data subsets by leveraging training dynamics SA Siddiqui, N Rajkumar, T Maharaj, D Krueger, S Hooker arXiv preprint arXiv:2209.10015, 2022 | 23 | 2022 |
| Reclaiming the digital commons: A public data trust for training data A Chan, H Bradley, N Rajkumar Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 855-868, 2023 | 14 | 2023 |
| Visibility into AI Agents A Chan, C Ezell, M Kaufmann, K Wei, L Hammond, H Bradley, E Bluemke, ... The 2024 ACM Conference on Fairness, Accountability, and Transparency, 958-973, 2024 | 6 | 2024 |
| Evaluating the text-to-SQL capabilities of large language models. arXiv N Rajkumar, R Li, D Bahdanau arXiv preprint arXiv:2204.00498, 2022 | 5 | 2022 |
| Myriad: a real-world testbed to bridge trajectory optimization and deep learning N Howe, S Dufort-Labbé, N Rajkumar, PL Bacon Advances in Neural Information Processing Systems 35, 29801-29815, 2022 | 4 | 2022 |
| A New National Purpose: Innovation Can Power the Future of Britain J Kakkad, B Macon-Cooney, J Northend, J Phillips, N Rajkumar, L Stanley, ... Tony Blair Institute for Global Change, 2023 | 2 | 2023 |
| IDs for AI Systems A Chan, N Kolt, P Wills, U Anwar, CS de Witt, N Rajkumar, L Hammond, ... arXiv preprint arXiv:2406.12137, 2024 | | 2024 |
| Self-supervision for data interpretability in image classification and sample efficiency in reinforcement learning N Rajkumar Université de Montréal, 2021 | | 2021 |
| RL: Generic reinforcement learning codebase in TensorFlow BM Li, A Cowen-Rivers, P Kozakowski, D Tao, SR Kamalakara, ... Journal of Open Source Software 4 (42), 1524, 2019 | | 2019 |
David Scott KruegerUniversity Assistant Professor, University of CambridgeVerified email at cam.ac.uk
