| 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 | 432 | 2017 |
| Statsnowball: a statistical approach to extracting entity relationships J Zhu, Z Nie, X Liu, B Zhang, JR Wen Proceedings of the 18th international conference on World wide web, 101-110, 2009 | 405 | 2009 |
| Event extraction as machine reading comprehension J Liu, Y Chen, K Liu, W Bi, X Liu Proceedings of the 2020 conference on empirical methods in natural language …, 2020 | 356 | 2020 |
| Automatically solving number word problems by semantic parsing and reasoning S Shi, Y Wang, CY Lin, X Liu, Y Rui Proceedings of the 2015 conference on empirical methods in natural language …, 2015 | 227 | 2015 |
| Translating a math word problem to an expression tree L Wang, Y Wang, D Cai, D Zhang, X Liu Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018 | 201 | 2018 |
| Automated social networking graph mining and visualization Z Nie, Y Cao, G Luo, R Zhang, X Liu, Y Ma, B Zhang, YQ Xu, JR Wen US Patent 9,990,429, 2018 | 162 | 2018 |
| 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 |
| Skeleton-to-response: Dialogue generation guided by retrieval memory D Cai, Y Wang, W Bi, Z Tu, X Liu, W Lam, S Shi Proceedings of the 2019 Conference of the North American Chapter of the …, 2018 | 94 | 2018 |
| Tablegpt: Few-shot table-to-text generation with table structure reconstruction and content matching H Gong, Y Sun, X Feng, B Qin, W Bi, X Liu, T Liu Proceedings of the 28th International Conference on Computational …, 2020 | 92 | 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 | 90 | 2019 |
| Coating of α-MoO3 on nitrogen-doped carbon nanotubes by electrodeposition as a high-performance cathode material for lithium-ion batteries H Zhang, X Liu, R Wang, R Mi, S Li, Y Cui, Y Deng, J Mei, H Liu Journal of Power Sources 274, 1063-1069, 2015 | 80 | 2015 |
| A batch normalized inference network keeps the KL vanishing away Q Zhu, J Su, W Bi, X Liu, X Ma, X Li, D Wu arXiv preprint arXiv:2004.12585, 2020 | 79 | 2020 |
| 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 |
| Improving knowledge-aware dialogue generation via knowledge base question answering J Wang, J Liu, W Bi, X Liu, K He, R Xu, M Yang Proceedings of the AAAI conference on artificial intelligence 34 (05), 9169-9176, 2020 | 64 | 2020 |
| Generating multiple diverse responses for short-text conversation J Gao, W Bi, X Liu, J Li, S Shi Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 6383-6390, 2019 | 62 | 2019 |
| 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 Advances in Neural Information Processing Systems 35, 3082-3095, 2022 | 59 | 2022 |
| Rigid formats controlled text generation P Li, H Zhang, X Liu, S Shi Proceedings of the 58th annual meeting of the association for computational …, 2020 | 59 | 2020 |
| A Discrete CVAE for Response Generation on Short-Text Conversation J Gao, W Bi, X Liu, J Li, G Zhou, S Shi Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 54 | 2019 |
| 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 | 45 | 2020 |
| Web-scale entity relationship extraction that extracts pattern (s) based on an extracted tuple Z Nie, X Liu, J Zhu, JR Wen US Patent 8,504,490, 2013 | 41* | 2013 |
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