| Towards understanding label smoothing Y Xu, Y Xu, Q Qian, H Li, R Jin arXiv preprint arXiv:2006.11653, 2020 | 26 | 2020 |
| Unsupervised visual representation learning by online constrained k-means Q Qian, Y Xu, J Hu, H Li, R Jin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 9 | 2022 |
| mplug-owl: Modularization empowers large language models with multimodality Q Ye, H Xu, G Xu, J Ye, M Yan, Y Zhou, J Wang, A Hu, P Shi, Y Shi, C Li, ... arXiv preprint arXiv:2304.14178, 2023 | 7 | 2023 |
| An empirical study on distribution shift robustness from the perspective of pre-training and data augmentation Z Liu, Y Xu, Y Xu, Q Qian, H Li, R Jin, X Ji, AB Chan arXiv preprint arXiv:2205.12753, 2022 | 5 | 2022 |
| mplug-2: A modularized multi-modal foundation model across text, image and video H Xu, Q Ye, M Yan, Y Shi, J Ye, Y Xu, C Li, B Bi, Q Qian, W Wang, G Xu, ... arXiv preprint arXiv:2302.00402, 2023 | 4 | 2023 |
| Improved fine-tuning by leveraging pre-training data: Theory and practice Z Liu, Y Xu, Y Xu, Q Qian, H Li, A Chan, R Jin arXiv preprint arXiv:2111.12292, 2021 | 4 | 2021 |
| Weakly supervised representation learning with coarse labels Y Xu, Q Qian, H Li, R Jin, J Hu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 3 | 2021 |
| K2NN: Self-Supervised Learning with Hierarchical Nearest Neighbors for Remote Sensing J Yuan, Y Xu, Z Wang ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 1 | 2023 |
| Representation Learning with Fine-grained Patterns Y Xu, Q Qian, H Li, R Jin, J Hu arXiv preprint ArXiv:2005.09681, 2020 | 1 | 2020 |
| Improved Visual Fine-tuning with Natural Language Supervision J Wang, Y Xu, J Hu, M Yan, J Sang, Q Qian arXiv preprint arXiv:2304.01489, 2023 | | 2023 |
