| Network trimming: A data-driven neuron pruning approach towards efficient deep architectures H Hu, R Peng, YW Tai, CK Tang arXiv preprint arXiv:1607.03250, 2016 | 1065 | 2016 |
| Human-level play in the game of Diplomacy by combining language models with strategic reasoning Meta Fundamental AI Research Diplomacy Team (FAIR)†, A Bakhtin, ... Science 378 (6624), 1067-1074, 2022 | 180 | 2022 |
| “Other-Play” for Zero-Shot Coordination H Hu, A Lerer, A Peysakhovich, J Foerster International Conference on Machine Learning, 4399-4410, 2020 | 167 | 2020 |
| Trajectory diversity for zero-shot coordination A Lupu, B Cui, H Hu, J Foerster International Conference on Machine Learning, 7204-7213, 2021 | 91 | 2021 |
| Simplified action decoder for deep multi-agent reinforcement learning H Hu, JN Foerster ICLR 2019, 2019 | 91 | 2019 |
| Improving policies via search in cooperative partially observable games A Lerer, H Hu, J Foerster, N Brown Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 7187-7194, 2020 | 76 | 2020 |
| Hierarchical decision making by generating and following natural language instructions H Hu, D Yarats, Q Gong, Y Tian, M Lewis Advances in neural information processing systems 32, 2019 | 62 | 2019 |
| Off-belief learning H Hu, A Lerer, B Cui, L Pineda, N Brown, J Foerster International Conference on Machine Learning, 4369-4379, 2021 | 58 | 2021 |
| Polygames: Improved zero learning T Cazenave, YC Chen, GW Chen, SY Chen, XD Chiu, J Dehos, M Elsa, ... ICGA Journal 42 (4), 244-256, 2020 | 49 | 2020 |
| Modeling strong and human-like gameplay with KL-regularized search AP Jacob, DJ Wu, G Farina, A Lerer, H Hu, A Bakhtin, J Andreas, N Brown International Conference on Machine Learning, 9695-9728, 2022 | 45 | 2022 |
| Language instructed reinforcement learning for human-ai coordination H Hu, D Sadigh International Conference on Machine Learning, 13584-13598, 2023 | 43 | 2023 |
| K-level Reasoning for Zero-Shot Coordination in Hanabi B Cui, H Hu, L Pineda, J Foerster Advances in Neural Information Processing Systems 34, 8215-8228, 2021 | 30 | 2021 |
| Ridge rider: Finding diverse solutions by following eigenvectors of the hessian J Parker-Holder, L Metz, C Resnick, H Hu, A Lerer, A Letcher, ... Advances in Neural Information Processing Systems 33, 753-765, 2020 | 25 | 2020 |
| Scalable online planning via reinforcement learning fine-tuning A Fickinger, H Hu, B Amos, S Russell, N Brown Advances in Neural Information Processing Systems 34, 16951-16963, 2021 | 16 | 2021 |
| Adversarial diversity in hanabi B Cui, A Lupu, S Sokota, H Hu, DJ Wu, JN Foerster The Eleventh International Conference on Learning Representations, 2023 | 12 | 2023 |
| Toward grounded commonsense reasoning M Kwon, H Hu, V Myers, S Karamcheti, A Dragan, D Sadigh International Conference on Robotics and Automation (ICRA), 2024 | 9* | 2024 |
| A fine-tuning approach to belief state modeling S Sokota, H Hu, DJ Wu, JZ Kolter, JN Foerster, N Brown International Conference on Learning Representations, 2022 | 8 | 2022 |
| Learned belief search: Efficiently improving policies in partially observable settings H Hu, A Lerer, N Brown, J Foerster arXiv preprint arXiv:2106.09086, 2021 | 8 | 2021 |
| Human-AI Coordination via Human-Regularized Search and Learning H Hu, DJ Wu, A Lerer, J Foerster, N Brown arXiv preprint arXiv:2210.05125, 2022 | 5 | 2022 |
| The Update Equivalence Framework for Decision-Time Planning S Sokota, G Farina, DJ Wu, H Hu, KA Wang, JZ Kolter, N Brown arXiv preprint arXiv:2304.13138, 2023 | 3 | 2023 |
Jakob FoersterAssociate Professor, University of OxfordVerified email at eng.ox.ac.uk
