| Learning from crowds by modeling common confusions Z Chu, J Ma, H Wang Proceedings of the AAAI Conference on Artificial Intelligence 35 (7), 5832-5840, 2021 | 40 | 2021 |
| CN-Probase: a data-driven approach for large-scale Chinese taxonomy construction J Chen, A Wang, J Chen, Y Xiao, Z Chu, J Liu, J Liang, W Wang 2019 IEEE 35th International Conference on Data Engineering (ICDE), 1706-1709, 2019 | 33 | 2019 |
| Meta policy learning for cold-start conversational recommendation Z Chu, H Wang, Y Xiao, B Long, L Wu Proceedings of the Sixteenth ACM International Conference on Web Search and …, 2023 | 24 | 2023 |
| Insrl: A multi-view learning framework fusing multiple information sources for distantly-supervised relation extraction Z Chu, H Jiang, Y Xiao, W Wang arXiv preprint arXiv:2012.09370, 2020 | 9 | 2020 |
| Improve Learning from Crowds via Generative Augmentation C Zhendong, W Hongning Proceedings of the 27th ACM SIGKDDConference on Knowledge Discovery and Data …, 2021 | 8 | 2021 |
| Meta-reinforcement learning via exploratory task clustering Z Chu, R Cai, H Wang Proceedings of the AAAI Conference on Artificial Intelligence 38 (10), 11633 …, 2024 | 4 | 2024 |
| Accounting for temporal dynamics in document streams Z Chu, R Cai, H Wang Proceedings of the 28th ACM International Conference on Information and …, 2019 | 2 | 2019 |
| Improving a Named Entity Recognizer Trained on Noisy Data with a Few Clean Instances Z Chu, R Zhang, T Yu, R Jain, VI Morariu, J Gu, A Nenkova arXiv preprint arXiv:2310.16790, 2023 | 1 | 2023 |
| MiddleGAN: Generate Domain Agnostic Samples for Unsupervised Domain Adaptation Y Gao, Z Chu, H Wang, J Stankovic arXiv preprint arXiv:2211.03144, 2022 | 1 | 2022 |
| Self-Cleaning: Improving a Named Entity Recognizer Trained on Noisy Data with a Few Clean Instances Z Chu, R Zhang, T Yu, R Jain, V Morariu, J Gu, A Nenkova Findings of the Association for Computational Linguistics: NAACL 2024, 196-210, 2024 | | 2024 |
| Improve Temporal Awareness of LLMs for Sequential Recommendation Z Chu, Z Wang, R Zhang, Y Ji, H Wang, T Sun 1st ICML Workshop on In-Context Learning, 2024 | | 2024 |
| Multi-objective intrinsic reward learning for conversational recommender systems Z Chu, N Wang, H Wang Advances in Neural Information Processing Systems 36, 2024 | | 2024 |
Hongning WangAssociate Professor, Department of Computer Science, University of Virginia在 virginia.edu 的电子邮件经过验证
