| Perturbed Masking: Parameter-free Probing for Analyzing and Interpreting BERT Z Wu, Y Chen, B Kao, Q Liu arXiv preprint arXiv:2004.14786, 2020 | 109 | 2020 |
| Next: a neural network framework for next poi recommendation Z Zhang, C Li, Z Wu, A Sun, D Ye, X Luo Frontiers of Computer Science 14, 314-333, 2020 | 74 | 2020 |
| A Survey for In-context Learning Q Dong, L Li, D Dai, C Zheng, Z Wu, B Chang, X Sun, J Xu, Z Sui arXiv preprint arXiv:2301.00234, 2022 | 46 | 2022 |
| DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models S Gong, M Li, J Feng, Z Wu, LP Kong arXiv preprint arXiv:2210.08933, 2022 | 42 | 2022 |
| Good for misconceived reasons: An empirical revisiting on the need for visual context in multimodal machine translation Z Wu, L Kong, W Bi, X Li, B Kao Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 29* | 2021 |
| Towards practical open knowledge base canonicalization TH Wu, Z Wu, B Kao, P Yin Proceedings of the 27th ACM International Conference on Information and …, 2018 | 26 | 2018 |
| ZeroGen: Efficient Zero-shot Learning via Dataset Generation J Ye, J Gao, Q Li, H Xu, J Feng, Z Wu, T Yu, L Kong arXiv preprint arXiv:2202.07922, 2022 | 24 | 2022 |
| PERQ: Predicting, Explaining, and Rectifying Failed Questions in KB-QA Systems Z Wu, B Kao, TH Wu, P Yin, Q Liu ACM International Conference on Web Search and Data Mining (WSDM), 2020 | 12 | 2020 |
| Self-adaptive In-context Learning Z Wu, Y Wang, J Ye, L Kong arXiv preprint arXiv:2212.10375, 2022 | 8 | 2022 |
| ProGen: Progressive Zero-shot Dataset Generation via In-context Feedback J Ye, J Gao, J Feng, Z Wu, T Yu, L Kong arXiv preprint arXiv:2210.12329, 2022 | 8 | 2022 |
| COLO: A Contrastive Learning based Re-ranking Framework for One-Stage Summarization C An, M Zhong, Z Wu, Q Zhu, X Huang, X Qiu arXiv preprint arXiv:2209.14569, 2022 | 6 | 2022 |
| Compositional Exemplars for In-context Learning J Ye, Z Wu, J Feng, T Yu, L Kong arXiv preprint arXiv:2302.05698, 2023 | 5 | 2023 |
| OpenICL: An Open-Source Framework for In-context Learning Z Wu, YX Wang, J Ye, J Feng, J Xu, Y Qiao, Z Wu arXiv preprint arXiv:2303.02913, 2023 | 4 | 2023 |
| In-Context Learning with Many Demonstration Examples M Li, S Gong, J Feng, Y Xu, J Zhang, Z Wu, L Kong arXiv preprint arXiv:2302.04931, 2023 | 2 | 2023 |
| Lexical Knowledge Internalization for Neural Dialog Generation Z Wu, W Bi, X Li, L Kong, B Kao arXiv preprint arXiv:2205.01941, 2022 | 2 | 2022 |
| Cascaded Head-colliding Attention L Zheng, Z Wu, L Kong arXiv preprint arXiv:2105.14850, 2021 | 2 | 2021 |
| Explanation Regeneration via Information Bottleneck Q Li, Z Wu, L Kong, W Bi arXiv preprint arXiv:2212.09603, 2022 | 1 | 2022 |
| Unsupervised Explanation Generation via Correct Instantiations S Cheng, Z Wu, J Chen, Z Li, Y Liu, L Kong arXiv preprint arXiv:2211.11160, 2022 | 1 | 2022 |
| Mulce: Multi-level canonicalization with embeddings of open knowledge bases TH Wu, B Kao, Z Wu, X Feng, Q Song, C Chen Web Information Systems Engineering–WISE 2020: 21st International Conference …, 2020 | 1 | 2020 |
| Self-Guided Noise-Free Data Generation for Efficient Zero-Shot Learning J Gao, R Pi, LIN Yong, H Xu, J Ye, Z Wu, W ZHANG, X Liang, Z Li, L Kong The Eleventh International Conference on Learning Representations, 2023 | | 2023 |
Lingpeng KongGoogle DeepMind, The University of Hong KongVerified email at cs.hku.hk
