| 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 | 834 | 2023 |
| Softtriple loss: Deep metric learning without triplet sampling Q Qian, L Shang, B Sun, J Hu, H Li, R Jin Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 482 | 2019 |
| mplug-owl2: Revolutionizing multi-modal large language model with modality collaboration Q Ye, H Xu, J Ye, M Yan, A Hu, H Liu, Q Qian, J Zhang, F Huang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 339 | 2024 |
| Dash: Semi-supervised learning with dynamic thresholding Y Xu, L Shang, J Ye, Q Qian, YF Li, B Sun, H Li, R Jin International conference on machine learning, 11525-11536, 2021 | 284 | 2021 |
| Instant-teaching: An end-to-end semi-supervised object detection framework Q Zhou, C Yu, Z Wang, Q Qian, H Li Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 241 | 2021 |
| Fine-grained visual categorization via multi-stage metric learning Q Qian, R Jin, S Zhu, Y Lin Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015 | 187 | 2015 |
| Zen-nas: A zero-shot nas for high-performance image recognition M Lin, P Wang, Z Sun, H Chen, X Sun, Q Qian, H Li, R Jin Proceedings of the IEEE/CVF International Conference on Computer Vision, 347-356, 2021 | 186 | 2021 |
| 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, ... International Conference on Machine Learning, 38728-38748, 2023 | 129 | 2023 |
| Efficient distance metric learning by adaptive sampling and mini-batch stochastic gradient descent (SGD) Q Qian, R Jin, J Yi, L Zhang, S Zhu Machine Learning 99, 353-372, 2015 | 121 | 2015 |
| Ureader: Universal ocr-free visually-situated language understanding with multimodal large language model J Ye, A Hu, H Xu, Q Ye, M Yan, G Xu, C Li, J Tian, Q Qian, J Zhang, Q Jin, ... arXiv preprint arXiv:2310.05126, 2023 | 115 | 2023 |
| mplug-docowl: Modularized multimodal large language model for document understanding J Ye, A Hu, H Xu, Q Ye, M Yan, Y Dan, C Zhao, G Xu, C Li, J Tian, Q Qi, ... arXiv preprint arXiv:2307.02499, 2023 | 109 | 2023 |
| Dr loss: Improving object detection by distributional ranking Q Qian, L Chen, H Li, R Jin Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 106 | 2020 |
| Building decision trees for the multi-class imbalance problem TR Hoens, Q Qian, NV Chawla, ZH Zhou Advances in Knowledge Discovery and Data Mining: 16th Pacific-Asia …, 2012 | 99 | 2012 |
| Robust optimization over multiple domains Q Qian, S Zhu, J Tang, R Jin, B Sun, H Li Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4739-4746, 2019 | 82 | 2019 |
| Hitea: Hierarchical temporal-aware video-language pre-training Q Ye, G Xu, M Yan, H Xu, Q Qian, J Zhang, F Huang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 75 | 2023 |
| Rbgnet: Ray-based grouping for 3d object detection H Wang, S Shi, Z Yang, R Fang, Q Qian, H Li, B Schiele, L Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 69 | 2022 |
| Learning to rank proposals for object detection Z Tan, X Nie, Q Qian, N Li, H Li Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 61 | 2019 |
| Semi-supervised clustering by input pattern assisted pairwise similarity matrix completion J Yi, L Zhang, R Jin, Q Qian, A Jain International conference on machine learning, 1400-1408, 2013 | 55 | 2013 |
| mplug-owl3: Towards long image-sequence understanding in multi-modal large language models J Ye, H Xu, H Liu, A Hu, M Yan, Q Qian, J Zhang, F Huang, J Zhou arXiv preprint arXiv:2408.04840, 2024 | 52 | 2024 |
| Improved fine-tuning by better leveraging pre-training data Z Liu, Y Xu, Y Xu, Q Qian, H Li, X Ji, A Chan, R Jin Advances in Neural Information Processing Systems 35, 32568-32581, 2022 | 52* | 2022 |
Rong JinAlibaba GroupΗ διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα cse.msu.edu
