| End-to-End Task-Completion Neural Dialogue Systems X Li, YN Chen, L Li, J Gao, A Celikyilmaz The 8th International Joint Conference on Natural Language Processing …, 2017 | 245 | 2017 |
| Towards end-to-end reinforcement learning of dialogue agents for information access B Dhingra, L Li, X Li, J Gao, YN Chen, F Ahmed, L Deng arXiv preprint arXiv:1609.00777, 2016 | 235 | 2016 |
| Bbq-networks: Efficient exploration in deep reinforcement learning for task-oriented dialogue systems Z Lipton, X Li, J Gao, L Li, F Ahmed, L Deng Thirty-Second AAAI Conference on Artificial Intelligence, 2018 | 149* | 2018 |
| Advances in smartphone-based point-of-care diagnostics X Xu, A Akay, H Wei, SQ Wang, B Pingguan-Murphy, BE Erlandsson, ... Proceedings of the IEEE 103 (2), 236-247, 2015 | 143 | 2015 |
| Composite task-completion dialogue policy learning via hierarchical deep reinforcement learning B Peng, X Li, L Li, J Gao, A Celikyilmaz, S Lee, KF Wong arXiv preprint arXiv:1704.03084, 2017 | 115 | 2017 |
| Generating informative and diverse conversational responses via adversarial information maximization Y Zhang, M Galley, J Gao, Z Gan, X Li, C Brockett, B Dolan Advances in Neural Information Processing Systems 31, 1810-1820, 2018 | 113 | 2018 |
| A user simulator for task-completion dialogues X Li, ZC Lipton, B Dhingra, L Li, J Gao, YN Chen arXiv preprint arXiv:1612.05688, 2016 | 85 | 2016 |
| Interactive Semantic Parsing for If-Then Recipes via Hierarchical Reinforcement Learning Z Yao, X Li, J Gao, B Sadler, H Sun arXiv preprint arXiv:1808.06740, 2018 | 81* | 2018 |
| Deep dyna-q: Integrating planning for task-completion dialogue policy learning B Peng, X Li, J Gao, J Liu, KF Wong, SY Su arXiv preprint arXiv:1801.06176, 2018 | 79 | 2018 |
| End-to-end joint learning of natural language understanding and dialogue manager X Yang, YN Chen, D Hakkani-Tür, P Crook, X Li, J Gao, L Deng 2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 64 | 2017 |
| Switch-based Active Deep Dyna-Q: Efficient Adaptive Planning for Task-Completion Dialogue Policy Learning Y Wu, X Li, J Liu, J Gao, Y Yang AAAI 2019, 2019 | 59* | 2019 |
| Recurrent reinforcement learning: a hybrid approach X Li, L Li, J Gao, X He, J Chen, L Deng, J He arXiv preprint arXiv:1509.03044, 2015 | 56 | 2015 |
| Tactical rewind: Self-correction via backtracking in vision-and-language navigation L Ke, X Li, Y Bisk, A Holtzman, Z Gan, J Liu, J Gao, Y Choi, S Srinivasa Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 55 | 2019 |
| Convlab: Multi-domain end-to-end dialog system platform S Lee, Q Zhu, R Takanobu, X Li, Y Zhang, Z Zhang, J Li, B Peng, X Li, ... arXiv preprint arXiv:1904.08637, 2019 | 48* | 2019 |
| Discriminative deep dyna-q: Robust planning for dialogue policy learning SY Su, X Li, J Gao, J Liu, YN Chen arXiv preprint arXiv:1808.09442, 2018 | 35 | 2018 |
| Subgoal discovery for hierarchical dialogue policy learning D Tang, X Li, J Gao, C Wang, L Li, T Jebara arXiv preprint arXiv:1804.07855, 2018 | 31 | 2018 |
| Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks X Li, X Yin, C Li, P Zhang, X Hu, L Zhang, L Wang, H Hu, L Dong, F Wei, ... European Conference on Computer Vision, 121-137, 2020 | 28 | 2020 |
| Joint language understanding and dialogue management using binary classification based on forward and backward recurrent neural network X Li, PA Crook, L Deng, J Gao, YN Chen, X Yang US Patent 10,268,679, 2019 | 28* | 2019 |
| Adversarial advantage actor-critic model for task-completion dialogue policy learning B Peng, X Li, J Gao, J Liu, YN Chen, KF Wong 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 28 | 2018 |
| Devices and methods for multiplexed assays GM Whitesides, KA Mirica, AW Martinez, C Cheng, ST Phillips, ... US Patent 8,821,810, 2014 | 27 | 2014 |
Jianfeng GaoMicrosoft Research, RedmondVerified email at microsoft.com
