| 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 | 1383 | 2020 |
| 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 | 740 | 2018 |
| 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 | 496 | 2020 |
| 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 | 488 | 2021 |
| 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 | 234 | 2017 |
| A study of reinforcement learning for neural machine translation L Wu, F Tian, T Qin, J Lai, TY Liu EMNLP-2018, 2018 | 211 | 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 | 168 | 2019 |
| Adversarial neural machine translation L Wu, Y Xia, L Zhao, F Tian, T Qin, J Lai, TY Liu ACML-2018, 2018 | 159 | 2018 |
| Learning to teach with dynamic loss functions L Wu, F Tian, Y Xia, Y Fan, T Qin, J Lai, TY Liu NeurIPS-2018, 2018 | 142 | 2018 |
| A survey on non-autoregressive generation for neural machine translation and beyond Y Xiao, L Wu, J Guo, J Li, M Zhang, T Qin, T Liu TPAMI-2023, 2022 | 91 | 2022 |
| Dual-view molecule pre-training J Zhu, Y Xia, L Wu, S Xie, T Qin, W Zhou, H Li, TY Liu KDD-2023, 2021 | 91* | 2021 |
| Multimodal sentiment analysis with unidirectional modality translation B Yang, B Shao, L Wu, X Lin Neurocomputing 467, 130-137, 2022 | 71 | 2022 |
| 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 | 71 | 2019 |
| Unified 2D and 3D Pre-Training of Molecular Representations J Zhu, Y Xia, L Wu, S Xie, T Qin, W Zhou, H Li, TY Liu KDD-2022, 2022 | 70 | 2022 |
| MolXPT: Wrapping Molecules with Text for Generative Pre-training Z Liu, W Zhang, Y Xia, L Wu, S Xie, T Qin, M Zhang, TY Liu ACL-2023, 2023 | 67 | 2023 |
| Masked contrastive representation learning for reinforcement learning J Zhu, Y Xia, L Wu, J Deng, W Zhou, T Qin, H Li TPAMI-2022, 2020 | 63 | 2020 |
| BioT5: Enriching Cross-modal Integration in Biology with Chemical Knowledge and Natural Language Associations Q Pei, W Zhang, J Zhu, K Wu, K Gao, L Wu, Y Xia, R Yan EMNLP-2023, 2023 | 57 | 2023 |
| Efficient sequence learning with group recurrent networks F Gao, L Wu, L Zhao, T Qin, X Cheng, TY Liu NAACL-2018, 799-808, 2018 | 57 | 2018 |
| Multimodal sentiment analysis with two-phase multi-task learning B Yang, L Wu, J Zhu, B Shao, X Lin, TY Liu IEEE/ACM Transactions on Audio, Speech, and Language Processing 30, 2015-2024, 2022 | 56 | 2022 |
| Direct molecular conformation generation J Zhu, Y Xia, C Liu, L Wu, S Xie, T Wang, Y Wang, W Zhou, T Qin, H Li, ... TMLR, 2022 | 56 | 2022 |
Tao QinPartner Research Manager, Microsoft Researchmicrosoft.com의 이메일 확인됨