| Siren's song in the AI ocean: a survey on hallucination in large language models Y Zhang, Y Li, L Cui, D Cai, L Liu, T Fu, X Huang, E Zhao, Y Zhang, ... arXiv preprint arXiv:2309.01219, 2023 | 455 | 2023 |
| Exploiting cross-sentence context for neural machine translation L Wang, Z Tu, A Way, Q Liu arXiv preprint arXiv:1704.04347, 2017 | 228 | 2017 |
| Convolutional self-attention networks B Yang, L Wang, D Wong, LS Chao, Z Tu arXiv preprint arXiv:1904.03107, 2019 | 137 | 2019 |
| UM-Corpus: A Large English-Chinese Parallel Corpus for Statistical Machine Translation. L Tian, DF Wong, LS Chao, P Quaresma, F Oliveira, L Yi, S Li, Y Wang, ... LREC, 1837-1842, 2014 | 131 | 2014 |
| Understanding and improving lexical choice in non-autoregressive translation L Ding, L Wang, X Liu, DF Wong, D Tao, Z Tu arXiv preprint arXiv:2012.14583, 2020 | 110 | 2020 |
| Document-level machine translation with large language models L Wang, C Lyu, T Ji, Z Zhang, D Yu, S Shi, Z Tu arXiv preprint arXiv:2304.02210, 2023 | 97 | 2023 |
| Modeling recurrence for transformer J Hao, X Wang, B Yang, L Wang, J Zhang, Z Tu arXiv preprint arXiv:1904.03092, 2019 | 91 | 2019 |
| Self-attention with structural position representations X Wang, Z Tu, L Wang, S Shi arXiv preprint arXiv:1909.00383, 2019 | 76 | 2019 |
| Self-attention with cross-lingual position representation L Ding, L Wang, D Tao arXiv preprint arXiv:2004.13310, 2020 | 74 | 2020 |
| Context-aware cross-attention for non-autoregressive translation L Ding, L Wang, D Wu, D Tao, Z Tu arXiv preprint arXiv:2011.00770, 2020 | 69 | 2020 |
| Rejuvenating low-frequency words: Making the most of parallel data in non-autoregressive translation L Ding, L Wang, X Liu, DF Wong, D Tao, Z Tu arXiv preprint arXiv:2106.00903, 2021 | 60 | 2021 |
| Redistributing low-frequency words: Making the most of monolingual data in non-autoregressive translation L Ding, L Wang, S Shi, D Tao, Z Tu Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022 | 56 | 2022 |
| Dynamic layer aggregation for neural machine translation with routing-by-agreement ZY Dou, Z Tu, X Wang, L Wang, S Shi, T Zhang Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 86-93, 2019 | 53 | 2019 |
| Zefeng Du, Shuming Shi, and Zhaopeng Tu. Macaw-llm: Multi-modal language modeling with image, audio, video, and text integration C Lyu, M Wu, L Wang, X Huang, B Liu arXiv preprint arXiv:2306.09093 1 (2), 6, 2023 | 52 | 2023 |
| Translating pro-drop languages with reconstruction models L Wang, Z Tu, S Shi, T Zhang, Y Graham, Q Liu Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 48 | 2018 |
| A novel approach to dropped pronoun translation L Wang, Z Tu, X Zhang, H Li, A Way, Q Liu arXiv preprint arXiv:1604.06285, 2016 | 48 | 2016 |
| Progressive multi-granularity training for non-autoregressive translation L Ding, L Wang, X Liu, DF Wong, D Tao, Z Tu arXiv preprint arXiv:2106.05546, 2021 | 43 | 2021 |
| Towards understanding neural machine translation with word importance S He, Z Tu, X Wang, L Wang, MR Lyu, S Shi arXiv preprint arXiv:1909.00326, 2019 | 43 | 2019 |
| Macaw-llm: Multi-modal language modeling with image, audio, video, and text integration C Lyu, M Wu, L Wang, X Huang, B Liu, Z Du, S Shi, Z Tu arXiv preprint arXiv:2306.09093, 2023 | 42 | 2023 |
| Assessing the ability of self-attention networks to learn word order B Yang, L Wang, DF Wong, LS Chao, Z Tu arXiv preprint arXiv:1906.00592, 2019 | 42 | 2019 |
Zhaopeng TuPrincipal Researcher, Tencent AI Lab在 tencent.com 的电子邮件经过验证
