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 | 376 | 2017 |
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 | 187 | 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 | 180 | 2018 |
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 | 156 | 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 | 148* | 2022 |
A survey on retrieval-augmented text generation H Li, Y Su, D Cai, Y Wang, L Liu arXiv preprint arXiv:2202.01110, 2022 | 137* | 2022 |
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, Z Tu, S Shi arXiv preprint arXiv:2305.19118, 2023 | 134 | 2023 |
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 Proceedings of the 57th annual meeting of the association for computational …, 2019 | 107 | 2019 |
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 | 104 | 2021 |
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 | 97* | 2022 |
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 | 97* | 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 | 88 | 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 | 85 | 2019 |
Neural machine translation with monolingual translation memory D Cai, Y Wang, H Li, W Lam, L Liu arXiv preprint arXiv:2105.11269, 2021 | 84 | 2021 |
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 | 65* | 2022 |
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 | 60 | 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 | 44 | 2021 |
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 | 41 | 2020 |
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 | 41 | 2020 |
Prototype-to-style: Dialogue generation with style-aware editing on retrieval memory Y Su, Y Wang, D Cai, S Baker, A Korhonen, N Collier IEEE/ACM Transactions on Audio, Speech, and Language Processing 29, 2152-2161, 2021 | 35 | 2021 |