| Achieving human parity on automatic chinese to english news translation H Hassan, A Aue, C Chen, V Chowdhary, J Clark, C Federmann, X Huang, ... arXiv preprint arXiv:1803.05567, 2018 | 537 | 2018 |
| Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection X Li, W Wang, L Wu, S Chen, X Hu, J Li, J Tang, J Yang NeurIPS-2020, 2020 | 351 | 2020 |
| Incorporating bert into neural machine translation J Zhu, Y Xia, L Wu, D He, T Qin, W Zhou, H Li, TY Liu ICLR-2020, 2020 | 321 | 2020 |
| Deliberation networks: Sequence generation beyond one-pass decoding Y Xia, F Tian, L Wu, J Lin, T Qin, N Yu, TY Liu NeurIPS-2017, 1782-1792, 2017 | 190 | 2017 |
| R-drop: Regularized dropout for neural networks L Xiaobo, L Wu, J Li, Y Wang, Q Meng, T Qin, W Chen, M Zhang, TY Liu Advances in Neural Information Processing Systems 34, 10890-10905, 2021 | 156 | 2021 |
| A study of reinforcement learning for neural machine translation L Wu, F Tian, T Qin, J Lai, TY Liu EMNLP-2018, 2018 | 154 | 2018 |
| Adversarial neural machine translation L Wu, Y Xia, L Zhao, F Tian, T Qin, J Lai, TY Liu ACML-2018, 2018 | 132 | 2018 |
| Soft contextual data augmentation for neural machine translation J Zhu, F Gao, L Wu, Y Xia, T Qin, W Zhou, X Cheng, TY Liu Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 103 | 2019 |
| Learning to teach with dynamic loss functions L Wu, F Tian, Y Xia, Y Fan, T Qin, J Lai, TY Liu NeurIPS-2018, 2018 | 94 | 2018 |
| Exploiting monolingual data at scale for neural machine translation L Wu, Y Wang, Y Xia, QIN Tao, J Lai, TY Liu EMNLP-2019, 4198-4207, 2019 | 50 | 2019 |
| Efficient sequence learning with group recurrent networks F Gao, L Wu, L Zhao, T Qin, X Cheng, TY Liu NAACL-2018, 799-808, 2018 | 42 | 2018 |
| Depth growing for neural machine translation L Wu, Y Wang, Y Xia, F Tian, F Gao, T Qin, J Lai, TY Liu ACL-2019, 2019 | 34 | 2019 |
| Beyond error propagation in neural machine translation: Characteristics of language also matter L Wu, X Tan, D He, F Tian, T Qin, J Lai, TY Liu EMNLP-2018, 2018 | 32* | 2018 |
| Word attention for sequence to sequence text understanding L Wu, F Tian, L Zhao, J Lai, TY Liu AAAI-2018 32 (1), 2018 | 25 | 2018 |
| Microsoft Research Asia's Systems for WMT19 Y Xia, X Tan, F Tian, F Gao, W Chen, Y Fan, L Gong, Y Leng, R Luo, ... WMT-2019, 2019 | 21 | 2019 |
| Transductive Ensemble Learning for Neural Machine Translation Y Wang, L Wu, Y Xia, T Qin, CX Zhai, TY Liu AAAI-2020, 2020 | 19 | 2020 |
| Sequence Prediction with Unlabeled Data by Reward Function Learning. L Wu, L Zhao, T Qin, J Lai, TY Liu IJCAI-2017, 3098-3104, 2017 | 19 | 2017 |
| Learning from Inside: Self-driven Siamese Sampling and Reasoning for Video Question Answering W Yu, H Zheng, M Li, L Ji, L Wu, N Xiao, N Duan Advances in Neural Information Processing Systems, NeurIPS-2021 34, 2021 | 16 | 2021 |
| Masked contrastive representation learning for reinforcement learning J Zhu, Y Xia, L Wu, J Deng, W Zhou, T Qin, H Li TPAMI-2022, 2020 | 15 | 2020 |
| Multi-branch attentive transformer Y Fan, S Xie, Y Xia, L Wu, T Qin, XY Li, TY Liu arXiv preprint arXiv:2006.10270, 2020 | 14 | 2020 |
Tao QinSenior Principal Research Manager, Microsoft ResearchVerified email at microsoft.com
