| Pandagpt: One model to instruction-follow them all Y Su, T Lan, H Li, J Xu, Y Wang, D Cai arXiv preprint arXiv:2305.16355, 2023 | 277 | 2023 |
| A Survey on Retrieval-Augmented Text Generation H Li, Y Su, D Cai, Y Wang, L Liu arXiv preprint arXiv:2202.01110, 2022 | 212* | 2022 |
| Neural Machine Translation with Monolingual Translation Memory D Cai, Y Wang, H Li, W Lam, L Liu ACL (Outstanding Paper Award), 2021 | 105 | 2021 |
| Describe What to Change: A Text-guided Unsupervised Image-to-Image Translation Approach Y Liu, M De Nadai, D Cai, H Li, X Alameda-Pineda, N Sebe, B Lepri ACMM, 1357-1365, 2020 | 71 | 2020 |
| Learning to Break the Loop: Analyzing and Mitigating Repetitions for Neural Text Generation J Xu, X Liu, J Yan, D Cai, H Li, J Li NeurIPS, 2022 | 55 | 2022 |
| Evaluating Explanation Methods for Neural Machine Translation J Li, L Liu, H Li, G Li, G Huang, S Shi ACL, 2020 | 31 | 2020 |
| TranSmart: A Practical Interactive Machine Translation System G Huang, L Liu, X Wang, L Wang, H Li, Z Tu, C Huang, S Shi arXiv preprint arXiv:2105.13072, 2021 | 28 | 2021 |
| Assessing Dialogue Systems with Distribution Distances J Xiang, Y Liu, D Cai, H Li, D Lian, L Liu Findings of ACL, 2021 | 24 | 2021 |
| Balancing Quality and Human Involvement: An Effective Approach to Interactive Neural Machine Translation T Zhao, L Liu, G Huang, H Li, Y Liu, L GuiQuan, S Shi AAAI 34 (05), 9660-9667, 2020 | 23 | 2020 |
| GWLAN: General Word-Level AutocompletioN for Computer-Aided Translation H Li, L Liu, G Huang, S Shi ACL, 2021 | 21 | 2021 |
| Neural Machine Translation With Noisy Lexical Constraints H Li, G Huang, D Cai, L Liu TASLP 28, 1864-1874, 2020 | 18 | 2020 |
| TextBind: Multi-turn Interleaved Multimodal Instruction-following in the Wild H Li, S Li, D Cai, L Wang, L Liu, T Watanabe, Y Yang, S Shi Findings of ACL, 2023 | 14* | 2023 |
| Ngram Is Back: Residual Learning of Neural Text Generation with -gram Language Model H Li, D Cai, J Xu, T Watanabe Findings of EMNLP, 2022 | 12 | 2022 |
| Repetition In Repetition Out: Towards Understanding Neural Text Degeneration from the Data Perspective H Li, T Lan, Z Fu, D Cai, L Liu, N Collier, T Watanabe, Y Su NeurIPS, 2023 | 9 | 2023 |
| A Frustratingly Simple Decoding Method for Neural Text Generation H Yang, D Cai, H Li, W Bi, W Lam, S Shi LREC-COLING, 2023 | 7 | 2023 |
| Data Augmentation for Text Generation Without Any Augmented Data W Bi, H Li, J Huang ACL, 2021 | 7 | 2021 |
| On the Branching Bias of Syntax Extracted from Pre-trained Language Models H Li, L Liu, G Huang, S Shi Findings of EMNLP, 4473–4478, 2020 | 6 | 2020 |
| Investigating Data Variance in Evaluations of Automatic Machine Translation Metrics J Xiang, H Li, Y Liu, L Liu, G Huang, D Lian, S Shi Findings of ACL, 2022 | 4 | 2022 |
| ALR: A Retrieve-then-Reason Framework for Long-context Question Answering H Li, P Verga, P Sen, B Yang, V Viswanathan, P Lewis, T Watanabe, Y Su arXiv preprint arXiv:2410.03227, 2024 | 3 | 2024 |
| Visualizing the Relationship Between Encoded Linguistic Information and Task Performance J Xiang, H Li, D Lian, G Huang, T Watanabe, L Liu Findings of ACL, 2022 | 3 | 2022 |
Deng CAI-, Tencent AI Lab, The Chinese University of Hong Kong確認したメール アドレス: se.cuhk.edu.hk