| Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models J Li, D Li, S Savarese, S Hoi International conference on machine learning, 19730-19742, 2023 | 9561 | 2023 |
| Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation J Li, D Li, C Xiong, S Hoi International conference on machine learning, 12888-12900, 2022 | 7592 | 2022 |
| Align before fuse: Vision and language representation learning with momentum distillation J Li, R Selvaraju, A Gotmare, S Joty, C Xiong, SCH Hoi Advances in neural information processing systems 34, 9694-9705, 2021 | 3011 | 2021 |
| Instructblip: Towards general-purpose vision-language models with instruction tuning. arxiv 2023 W Dai, J Li, D Li, AMH Tiong, J Zhao, W Wang, B Li, P Fung, S Hoi arXiv preprint arXiv:2305.06500 2, 2023 | 2280* | 2023 |
| Dividemix: Learning with noisy labels as semi-supervised learning J Li, R Socher, SCH Hoi arXiv preprint arXiv:2002.07394, 2020 | 1592 | 2020 |
| Prototypical contrastive learning of unsupervised representations J Li, P Zhou, C Xiong, SCH Hoi arXiv preprint arXiv:2005.04966, 2020 | 1459 | 2020 |
| Codet5+: Open code large language models for code understanding and generation Y Wang, H Le, A Gotmare, N Bui, J Li, S Hoi Proceedings of the 2023 conference on empirical methods in natural language …, 2023 | 804 | 2023 |
| Blip-diffusion: Pre-trained subject representation for controllable text-to-image generation and editing D Li, J Li, S Hoi Advances in Neural Information Processing Systems 36, 30146-30166, 2023 | 473 | 2023 |
| Learning to Learn from Noisy Labeled Data J Li, Y Wong, Q Zhao, MS Kankanhalli The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 | 472 | 2019 |
| Comatch: Semi-supervised learning with contrastive graph regularization J Li, C Xiong, SCH Hoi Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 423 | 2021 |
| Longvideobench: A benchmark for long-context interleaved video-language understanding H Wu, D Li, B Chen, J Li Advances in Neural Information Processing Systems 37, 28828-28857, 2024 | 327 | 2024 |
| Align and prompt: Video-and-language pre-training with entity prompts D Li, J Li, H Li, JC Niebles, SCH Hoi Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 265 | 2022 |
| From images to textual prompts: Zero-shot visual question answering with frozen large language models J Guo, J Li, D Li, AMH Tiong, B Li, D Tao, S Hoi Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 264 | 2023 |
| The devil is in classification: A simple framework for long-tail instance segmentation T Wang, Y Li, B Kang, J Li, J Liew, S Tang, S Hoi, J Feng European conference on computer vision, 728-744, 2020 | 251 | 2020 |
| Ulip-2: Towards scalable multimodal pre-training for 3d understanding L Xue, N Yu, S Zhang, A Panagopoulou, J Li, R Martín-Martín, J Wu, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 212 | 2024 |
| Learning to detect human-object interactions with knowledge B Xu, Y Wong, J Li, Q Zhao, MS Kankanhalli Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 205 | 2019 |
| Learning from noisy data with robust representation learning J Li, C Xiong, SCH Hoi Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 165 | 2021 |
| Plug-and-play vqa: Zero-shot vqa by conjoining large pretrained models with zero training AMH Tiong, J Li, B Li, S Savarese, SCH Hoi arXiv preprint arXiv:2210.08773, 2022 | 163 | 2022 |
| Tackling data heterogeneity in federated learning with class prototypes Y Dai, Z Chen, J Li, S Heinecke, L Sun, R Xu Proceedings of the AAAI Conference on Artificial Intelligence 37 (6), 7314-7322, 2023 | 160 | 2023 |
| Mopro: Webly supervised learning with momentum prototypes J Li, C Xiong, SCH Hoi arXiv preprint arXiv:2009.07995, 2020 | 143 | 2020 |
