| Learning deep transformer models for machine translation Q Wang, B Li, T Xiao, J Zhu, C Li, DF Wong, LS Chao arXiv preprint arXiv:1906.01787, 2019 | 872 | 2019 |
| Multi-layer representation fusion for neural machine translation Q Wang, F Li, T Xiao, Y Li, Y Li, J Zhu arXiv preprint arXiv:2002.06714, 2020 | 59 | 2020 |
| The NiuTrans machine translation systems for WMT19 B Li, Y Li, C Xu, Y Lin, J Liu, H Liu, Z Wang, Y Zhang, N Xu, Z Wang, ... Proceedings of the Fourth Conference on Machine Translation (Volume 2 …, 2019 | 54 | 2019 |
| A simple and effective approach to coverage-aware neural machine translation Y Li, T Xiao, Y Li, Q Wang, C Xu, J Zhu Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018 | 21 | 2018 |
| Niuparser: A Chinese syntactic and semantic parsing toolkit J Zhu, M Zhu, Q Wang, T Xiao Proceedings of ACL-IJCNLP 2015 System Demonstrations, 145-150, 2015 | 16 | 2015 |
| Neural machine translation with joint representation Y Li, Q Wang, T Xiao, T Liu, J Zhu Proceedings of the AAAI conference on artificial intelligence 34 (05), 8285-8292, 2020 | 13 | 2020 |
| The niutrans machine translation system for wmt18 Q Wang, B Li, J Liu, B Jiang, Z Zhang, Y Li, Y Lin, T Xiao, J Zhu Proceedings of the Third Conference on Machine Translation: Shared Task …, 2018 | 11 | 2018 |
| Learning deep transformer models for machine translation (2019) Q Wang, B Li, T Xiao, J Zhu, C Li, DF Wong, LS Chao arXiv preprint arXiv:1906.01787, 2019 | 7 | 2019 |
| Revisiting the self-consistency challenges in multi-choice question formats for large language model evaluation W Zhou, Q Wang, M Xu, M Chen, X Duan Proceedings of the 2024 Joint International Conference on Computational …, 2024 | 6 | 2024 |
| Understanding and improving the robustness of terminology constraints in neural machine translation H Zhang, Q Wang, B Qin, Z Shi, H Wang, M Chen Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | 6 | 2023 |
| Hybrid-regressive neural machine translation Q Wang, X Hu, M Chen arXiv preprint arXiv:2210.10416, 2022 | 5 | 2022 |
| Learning decoupled retrieval representation for nearest neighbour neural machine translation Q Wang, R Weng, M Chen arXiv preprint arXiv:2209.08738, 2022 | 5 | 2022 |
| 面向神经机器翻译的集成学习方法分析 李北， 王强， 肖桐， 姜雨帆， 张哲旸， 刘继强， 张俐， 于清 中文信息学报 33 (3), 42-51, 2019 | 5 | 2019 |
| Training flexible depth model by multi-task learning for neural machine translation Q Wang, T Xiao, J Zhu arXiv preprint arXiv:2010.08265, 2020 | 4 | 2020 |
| 稀缺资源机器翻译中改进的语料级和短语级中间语言方法研究 李强， 王强， 肖桐， 朱靖波 计算机学报 40 (4), 925-938, 2017 | 4 | 2017 |
| Towards reliable neural machine translation with consistency-aware meta-learning R Weng, Q Wang, W Cheng, C Zhu, M Zhang Proceedings of the AAAI Conference on Artificial Intelligence 37 (11), 13709 …, 2023 | 3 | 2023 |
| Layer-wise multi-view learning for neural machine translation Q Wang, C Li, Y Zhang, T Xiao, J Zhu arXiv preprint arXiv:2011.01482, 2020 | 3 | 2020 |
| The RoyalFlush system for the WMT 2022 efficiency task B Qin, A Jia, Q Wang, J Lu, S Pan, H Wang, M Chen arXiv preprint arXiv:2212.01543, 2022 | 2 | 2022 |
| Hybrid-regressive paradigm for accurate and speed-robust neural machine translation Q Wang, X Hu, M Chen Findings of the Association for Computational Linguistics: ACL 2023, 5931-5945, 2023 | 1 | 2023 |
| Translation Memory Guided Neural Machine Translation S Kuang, H Yu, W Luo, Q Wang | 1 | 2021 |
Jingbo ZhuNortheastern University, ChinaVerified email at mail.neu.edu.cn