| Deep neural solver for math word problems Y Wang, X Liu, S Shi Proceedings of the 2017 conference on empirical methods in natural language …, 2017 | 433 | 2017 |
| Encouraging divergent thinking in large language models through multi-agent debate T Liang, Z He, W Jiao, X Wang, Y Wang, R Wang, Y Yang, S Shi, Z Tu arXiv preprint arXiv:2305.19118, 2023 | 310 | 2023 |
| A survey on retrieval-augmented text generation H Li, Y Su, D Cai, Y Wang, L Liu arXiv preprint arXiv:2202.01110, 2022 | 287* | 2022 |
| 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 | 280 | 2023 |
| A contrastive framework for neural text generation Y Su, T Lan, Y Wang, D Yogatama, L Kong, N Collier Advances in Neural Information Processing Systems 35, 21548-21561, 2022 | 234 | 2022 |
| Graph-to-tree learning for solving math word problems J Zhang, L Wang, RKW Lee, Y Bin, Y Wang, J Shao, EP Lim Proceedings of the 58th annual meeting of the association for computational …, 2020 | 213 | 2020 |
| Translating a math word problem to an expression tree L Wang, Y Wang, D Cai, D Zhang, X Liu arXiv preprint arXiv:1811.05632, 2018 | 201 | 2018 |
| BoB: BERT over BERT for training persona-based dialogue models from limited personalized data H Song, Y Wang, K Zhang, WN Zhang, T Liu arXiv preprint arXiv:2106.06169, 2021 | 136 | 2021 |
| Modeling intra-relation in math word problems with different functional multi-head attentions J Li, L Wang, J Zhang, Y Wang, BT Dai, D Zhang Association for Computational Linguistics, 2019 | 122 | 2019 |
| Language models can see: Plugging visual controls in text generation Y Su, T Lan, Y Liu, F Liu, D Yogatama, Y Wang, L Kong, N Collier arXiv preprint arXiv:2205.02655, 2022 | 117* | 2022 |
| Neural machine translation with monolingual translation memory D Cai, Y Wang, H Li, W Lam, L Liu arXiv preprint arXiv:2105.11269, 2021 | 108 | 2021 |
| Skeleton-to-response: Dialogue generation guided by retrieval memory D Cai, Y Wang, V Bi, Z Tu, X Liu, W Lam, S Shi Proceedings of NAACL-HLT, 2019 | 106* | 2019 |
| Generate, delete and rewrite: A three-stage framework for improving persona consistency of dialogue generation H Song, Y Wang, WN Zhang, X Liu, T Liu arXiv preprint arXiv:2004.07672, 2020 | 95 | 2020 |
| Retrieval-guided dialogue response generation via a matching-to-generation framework D Cai, Y Wang, W Bi, Z Tu, X Liu, S Shi Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 89 | 2019 |
| Mwptoolkit: An open-source framework for deep learning-based math word problem solvers Y Lan, L Wang, Q Zhang, Y Lan, BT Dai, Y Wang, D Zhang, EP Lim Proceedings of the AAAI Conference on Artificial Intelligence 36 (11), 13188 …, 2022 | 74* | 2022 |
| Large language models meet harry potter: A dataset for aligning dialogue agents with characters N Chen, Y Wang, H Jiang, D Cai, Y Li, Z Chen, L Wang, J Li Findings of the Association for Computational Linguistics: EMNLP 2023, 8506-8520, 2023 | 67* | 2023 |
| Improving open-domain dialogue systems via multi-turn incomplete utterance restoration Z Pan, K Bai, Y Wang, L Zhou, X Liu Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 66 | 2019 |
| Non-autoregressive text generation with pre-trained language models Y Su, D Cai, Y Wang, D Vandyke, S Baker, P Li, N Collier arXiv preprint arXiv:2102.08220, 2021 | 52 | 2021 |
| The world is not binary: Learning to rank with grayscale data for dialogue response selection Z Lin, D Cai, Y Wang, X Liu, HT Zheng, S Shi arXiv preprint arXiv:2004.02421, 2020 | 47 | 2020 |
| Dialogue response selection with hierarchical curriculum learning Y Su, D Cai, Q Zhou, Z Lin, S Baker, Y Cao, S Shi, N Collier, Y Wang arXiv preprint arXiv:2012.14756, 2020 | 45 | 2020 |
Deng CAI-, Tencent AI Lab, The Chinese University of Hong Kongכתובת אימייל מאומתת בדומיין se.cuhk.edu.hk