| A survey on 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 | 580 | 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 | 179 | 2022 |
| Perturbed Masking: Parameter-free Probing for Analyzing and Interpreting BERT Z Wu, Y Chen, B Kao, Q Liu arXiv preprint arXiv:2004.14786, 2020 | 162 | 2020 |
| Internlm: A multilingual language model with progressively enhanced capabilities ILM Team 2023-01-06)[2023-09-27]. https://github. com/InternLM/InternLM, 2023 | 115 | 2023 |
| 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 | 102 | 2022 |
| 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 | 88 | 2020 |
| 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 | 57* | 2021 |
| Opencompass: A universal evaluation platform for foundation models OC Contributors GitHub repository, 2023 | 56 | 2023 |
| Self-Adaptive In-Context Learning: An Information Compression Perspective for In-Context Example Selection and Ordering Z Wu, Y Wang, J Ye, L Kong | 56* | 2023 |
| Compositional exemplars for in-context learning J Ye, Z Wu, J Feng, T Yu, L Kong International Conference on Machine Learning, 39818-39833, 2023 | 48 | 2023 |
| Can We Edit Factual Knowledge by In-Context Learning? C Zheng, L Li, Q Dong, Y Fan, Z Wu, J Xu, B Chang arXiv preprint arXiv:2305.12740, 2023 | 45 | 2023 |
| 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 | 30 | 2018 |
| 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 | 29 | 2022 |
| Self-guided noise-free data generation for efficient zero-shot learning WZ J Gao, R Pi, L Yong, H Xu, J Ye, Z Wu The Eleventh International Conference on Learning Representations (ICLR 2023), 2023 | 25* | 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 | 20 | 2023 |
| 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 | 16 | 2020 |
| 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 | 13 | 2022 |
| SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents K Cheng, Q Sun, Y Chu, F Xu, Y Li, J Zhang, Z Wu arXiv preprint arXiv:2401.10935, 2024 | 8 | 2024 |
| Corex: Pushing the Boundaries of Complex Reasoning through Multi-Model Collaboration Q Sun, Z Yin, X Li, Z Wu, X Qiu, L Kong arXiv preprint arXiv:2310.00280, 2023 | 7 | 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 | 7 | 2023 |
Lingpeng KongGoogle DeepMind, The University of Hong KongVerifierad e-postadress på cs.hku.hk
