| Towards effective clustered federated learning: A peer-to-peer framework with adaptive neighbor matching Z Li, J Lu, S Luo, D Zhu, Y Shao, Y Li, Z Zhang, Y Wang, C Wu IEEE Transactions on Big Data, 2022 | 56* | 2022 |
| Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models D Zhu, Z Sun, Z Li, T Shen, K Yan, S Ding, K Kuang, C Wu ICML 2024, 2024 | 25 | 2024 |
| Universal domain adaptation via compressive attention matching D Zhu, Y Li, J Yuan, Z Li, K Kuang, C Wu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 25 | 2023 |
| Generalized Universal Domain Adaptation with Generative Flow Networks D Zhu, Y Li, Y Shao, J Hao, F Wu, K Kuang, J Xiao, C Wu ACM International Conference on Multimedia (MM) 2023, 2023 | 16 | 2023 |
| Neural collapse anchored prompt tuning for generalizable vision-language models D Zhu, Z Li, M Zhang, J Yuan, J Liu, K Kuang, C Wu Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | 11* | 2024 |
| Quantitatively Measuring and Contrastively Exploring Heterogeneity for Domain Generalization Y Tong, J Yuan, M Zhang, D Zhu, K Zhang, F Wu, K Kuang ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023, 2023 | 10 | 2023 |
| Ensemble federated adversarial training with non-iid data S Luo, D Zhu, Z Li, C Wu FTL-IJCAI 2021, 2021 | 8 | 2021 |
| Resmatch: Referring expression segmentation in a semi-supervised manner Y Zang, R Cao, C Fu, D Zhu, M Zhang, W Hu, L Zhu, T Chen Information Sciences 694, 121709, 2025 | 7 | 2025 |
| Merging loras like playing lego: Pushing the modularity of lora to extremes through rank-wise clustering Z Zhao, T Shen, D Zhu, Z Li, J Su, X Wang, K Kuang, F Wu arXiv preprint arXiv:2409.16167, 2024 | 3 | 2024 |
| Learn from Downstream and Be Yourself in Multimodal Large Language Model Fine-Tuning W Huang, J Liang, Z Shi, D Zhu, G Wan, H Li, B Du, D Tao, M Ye arXiv preprint arXiv:2411.10928, 2024 | 2 | 2024 |
| Mix Data or Merge Models? Balancing the Helpfulness, Honesty, and Harmlessness of Large Language Model via Model Merging J Yang, D Jin, A Tang, L Shen, D Zhu, Z Chen, D Wang, Q Cui, Z Zhang, ... arXiv preprint arXiv:2502.06876, 2025 | | 2025 |
| Let Human Sketches Help: Empowering Challenging Image Segmentation Task with Freehand Sketches Y Zang, R Cao, J Zhang, Y Han, Z Cao, W Hu, D Zhu, L Zhu, Z Li, D Ji, ... arXiv preprint arXiv:2501.19329, 2025 | | 2025 |
| REMEDY: Recipe Merging Dynamics in Large Vision-Language Models D Zhu, yibing Song, T Shen, Z Zhao, J Yang, M Zhang, C Wu ICLR 2025, 2025 | | 2025 |
| Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-Task Learning Z Zhao, Y Zhou, D Zhu, T Shen, X Wang, J Su, K Kuang, Z Wei, F Wu, ... arXiv preprint arXiv:2501.15103, 2025 | | 2025 |
| An Adaptive Aggregation Method for Federated Learning via Meta Controller T Shen, Z Li, Z Zhao, D Zhu, Z Lv, S Zhang, K Kuang, F Wu Proceedings of the 6th ACM International Conference on Multimedia in Asia …, 2024 | | 2024 |
| Mitigating the Backdoor Effect for Multi-Task Model Merging via Safety-Aware Subspace J Yang, A Tang, D Zhu, Z Chen, L Shen, F Wu arXiv preprint arXiv:2410.13910, 2024 | | 2024 |
| Improving Group Connectivity for Generalization of Federated Deep Learning Z Li, J Lin, Z Li, D Zhu, R Ye, T Shen, T Lin, C Wu arXiv preprint arXiv:2402.18949, 2024 | | 2024 |
| Towards effective clustered federated learning: A peer-to-peer framework with adaptive neighbor matching Z Li, J Lu, S Luo, D Zhu, Y Shao, Y Li, Z Zhang, Y Wang, C Wu IEEE Transactions on Big Data, 2022 | | 2022 |
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