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 | 1134 | 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 | 225 | 2022 |
“Other-Play” for Zero-Shot Coordination H Hu, A Lerer, A Peysakhovich, J Foerster International Conference on Machine Learning, 4399-4410, 2020 | 198 | 2020 |
Trajectory diversity for zero-shot coordination A Lupu, B Cui, H Hu, J Foerster International Conference on Machine Learning, 7204-7213, 2021 | 108 | 2021 |
Simplified action decoder for deep multi-agent reinforcement learning H Hu, JN Foerster ICLR 2019, 2019 | 99 | 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 | 85 | 2020 |
Off-belief learning H Hu, A Lerer, B Cui, L Pineda, N Brown, J Foerster International Conference on Machine Learning, 4369-4379, 2021 | 69 | 2021 |
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 | 67 | 2019 |
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 | 59 | 2022 |
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 | 59 | 2020 |
Language instructed reinforcement learning for human-ai coordination H Hu, D Sadigh International Conference on Machine Learning, 13584-13598, 2023 | 55 | 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 | 35 | 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 | 32 | 2020 |
Toward grounded commonsense reasoning M Kwon, H Hu, V Myers, S Karamcheti, A Dragan, D Sadigh International Conference on Robotics and Automation (ICRA), 2024 | 19* | 2024 |
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 | 19 | 2021 |
Imitation Bootstrapped Reinforcement Learning H Hu, S Mirchandani, D Sadigh Robotics: Science and Systems 2024, 2024 | 18 | 2024 |
Adversarial diversity in hanabi B Cui, A Lupu, S Sokota, H Hu, DJ Wu, JN Foerster The Eleventh International Conference on Learning Representations, 2023 | 17 | 2023 |
Learned belief search: Efficiently improving policies in partially observable settings H Hu, A Lerer, N Brown, J Foerster arXiv preprint arXiv:2106.09086, 2021 | 11 | 2021 |
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 | 10 | 2022 |
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 |