| Multi-label classification on tree-and dag-structured hierarchies W Bi, JT Kwok Proceedings of the 28th International Conference on Machine Learning (ICML …, 2011 | 246 | 2011 |
| 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 | 245 | 2020 |
| Efficient Multi-label Classification with Many Labels W Bi, JT Kwok Proceedings of the 30th International Conference on Machine Learning (ICML …, 2013 | 232 | 2013 |
| Large-scale Nyström kernel matrix approximation using randomized SVD M Li, W Bi, JT Kwok, BL Lu IEEE transactions on neural networks and learning systems 26 (1), 152-164, 2014 | 132 | 2014 |
| Efficient Training of Visual Transformers with Small-Size Datasets Y Liu, E Sangineto, W Bi, N Sebe, B Lepri, M De Nadai NeurIPS 2021, 2021 | 124* | 2021 |
| Multilabel Classification with Label Correlations and Missing Labels W Bi, JT Kwok Twenty-Eighth Conference on Artificial Intelligence, 2014 | 102 | 2014 |
| 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 | 74 | 2019 |
| Skeleton-to-Response: Dialogue Generation Guided by Retrieval Memory D Cai, Y Wang, V Bi, Z Tu, X Liu, W Lam, S Shi NAACL2019, 2018 | 74 | 2018 |
| Learning to Predict from Crowdsourced Data W Bi, L Wang, JT Kwok, Z Tu Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014 | 70 | 2014 |
| A batch normalized inference network keeps the kl vanishing away Q Zhu, J Su, W Bi, X Liu, X Ma, X Li, D Wu ACL2020, 2020 | 63 | 2020 |
| 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 | 61 | 2023 |
| 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, 6383-6390, 2019 | 56 | 2019 |
| Are Training Samples Correlated? Learning to Generate Dialogue Responses with Multiple References L Qiu, J Li, W Bi, D Zhao, R Yan ACL2019, 2019 | 52 | 2019 |
| Bayes-optimal hierarchical multilabel classification W Bi, TJ Kwok TKDE, 2015 | 52 | 2015 |
| 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 | 50 | 2020 |
| 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 | 49 | 2020 |
| A Discrete CVAE for Response Generation on Short-Text Conversation J Gao, W Bi, X Liu, J Li, G Zhou, S Shi EMNLP2019, 2019 | 48 | 2019 |
| Learning to Abstract for Memory-Augmented Conversational Response Generation Z Tian, W Bi, X Li, NL Zhang ACL2019, 2019 | 44 | 2019 |
| Extending semi-supervised learning methods for inductive transfer learning Y Shi, Z Lan, W Liu, W Bi 2009 Ninth IEEE international conference on data mining, 483-492, 2009 | 44 | 2009 |
| Learning to customize model structures for few-shot dialogue generation tasks Y Song, Z Liu, W Bi, R Yan, M Zhang arXiv preprint arXiv:1910.14326, 2019 | 40* | 2019 |
Xiaojiang LiuAppleVerified email at apple.com
