| Zoneout: Regularizing rnns by randomly preserving hidden activations D Krueger, T Maharaj, J Kramár, M Pezeshki, N Ballas, NR Ke, A Goyal, ... arXiv preprint arXiv:1606.01305, 2016 | 369 | 2016 |
| Reinforcement and imitation learning for diverse visuomotor skills Y Zhu, Z Wang, J Merel, A Rusu, T Erez, S Cabi, S Tunyasuvunakool, ... arXiv preprint arXiv:1802.09564, 2018 | 316 | 2018 |
| OpenSpiel: A framework for reinforcement learning in games M Lanctot, E Lockhart, JB Lespiau, V Zambaldi, S Upadhyay, J Pérolat, ... arXiv preprint arXiv:1908.09453, 2019 | 206 | 2019 |
| Guidelines for artificial intelligence containment J Babcock, J Kramar, RV Yampolskiy Next-Generation Ethics: Engineering a Better Society (Ed.) Ali. E. Abbas, 90-112, 2019 | 58 | 2019 |
| The AGI containment problem J Babcock, J Kramár, R Yampolskiy Artificial General Intelligence: 9th International Conference, AGI 2016, New …, 2016 | 49 | 2016 |
| Learning reciprocity in complex sequential social dilemmas T Eccles, E Hughes, J Kramár, S Wheelwright, JZ Leibo arXiv preprint arXiv:1903.08082, 2019 | 42 | 2019 |
| Learning to play no-press diplomacy with best response policy iteration T Anthony, T Eccles, A Tacchetti, J Kramár, I Gemp, T Hudson, N Porcel, ... Advances in Neural Information Processing Systems 33, 17987-18003, 2020 | 40 | 2020 |
| Negotiation and honesty in artificial intelligence methods for the board game of Diplomacy J Kramár, T Eccles, I Gemp, A Tacchetti, KR McKee, M Malinowski, ... Nature Communications 13 (1), 7214, 2022 | 22 | 2022 |
| OpenSpiel: a framework for reinforcement learning in games. CoRR abs/1908.09453 (2019) M Lanctot, E Lockhart, JB Lespiau, V Zambaldi, S Upadhyay, J Pérolat, ... arXiv preprint arXiv:1908.09453, 2019 | 19 | 2019 |
| Reinforcement and imitation learning for a task S Tunyasuvunakool, Y Zhu, J Merel, J Kramar, Z Wang, NMO Heess US Patent App. 16/174,112, 2019 | 17 | 2019 |
| Tracr: Compiled transformers as a laboratory for interpretability D Lindner, J Kramár, M Rahtz, T McGrath, V Mikulik arXiv preprint arXiv:2301.05062, 2023 | 13 | 2023 |
| Sample-based approximation of Nash in large many-player games via gradient descent I Gemp, R Savani, M Lanctot, Y Bachrach, T Anthony, R Everett, ... arXiv preprint arXiv:2106.01285, 2021 | 11 | 2021 |
| The Imitation Game: Learned Reciprocity in Markov games. T Eccles, E Hughes, J Kramár, S Wheelwright, JZ Leibo AAMAS 19, 3, 2019 | 10 | 2019 |
| 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 | 8 | 2023 |
| Power-seeking can be probable and predictive for trained agents V Krakovna, J Kramar arXiv preprint arXiv:2304.06528, 2023 | 7 | 2023 |
| Explaining grokking through circuit efficiency V Varma, R Shah, Z Kenton, J Kramár, R Kumar arXiv preprint arXiv:2309.02390, 2023 | 6 | 2023 |
| A generalized-zero-preserving method for compact encoding of concept lattices M Skala, V Krakovna, J Kramár, G Penn Proceedings of the 48th annual meeting of the Association for Computational …, 2010 | 6 | 2010 |
| The hydra effect: Emergent self-repair in language model computations T McGrath, M Rahtz, J Kramar, V Mikulik, S Legg arXiv preprint arXiv:2307.15771, 2023 | 5 | 2023 |
| How intelligible is intelligence? A Salamon, S Rayhawk, J Kramár Proceedings of the VIII European conference on computing and philosophy …, 2010 | 4 | 2010 |
| A Neural Network Auction For Group Decision Making Over a Continuous Space. Y Bachrach, IM Gemp, M Garnelo, J Kramar, T Eccles, D Rosenbaum, ... IJCAI, 4976-4979, 2021 | 3 | 2021 |
