| Revisiting Weighted Aggregation in Federated Learning with Neural Networks Z Li, T Lin, X Shang, C Wu The Fortieth International Conference on Machine Learning (ICML 2023), 2023 | 70 | 2023 |
| No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier Z Li, X Shang, R He, T Lin, C Wu 2023 International Conference on Computer Vision (ICCV 2023), 2023 | 61 | 2023 |
| 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 | 57* | 2022 |
| OpenFedLLM: Training Large Language Models on Decentralized Private Data via Federated Learning R Ye, W Wang, J Chai, D Li, Z Li, Y Xu, Y Du, Y Wang, S Chen KDD 2024, 2024 | 55 | 2024 |
| Boosting the generalization ability of Vis-NIR-spectroscopy-based regression models through dimension reduction and transfer learning X Li*, Z Li*, X Yang, Y He Computers and Electronics in Agriculture 186, 106157, 2021 | 45 | 2021 |
| 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 | 27 | 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 | 24 | 2023 |
| WISE: Rethinking the Knowledge Memory for Lifelong Model Editing of Large Language Models P Wang*, Z Li*, N Zhang, Z Xu, Y Yao, Y Jiang, P Xie, F Huang, H Chen NeurIPS 2024, 2024 | 23 | 2024 |
| Can we share models if sharing data is not an option? Z Li, F Mao, C Wu Patterns, Cell Press 3 (11), 2022 | 19 | 2022 |
| Edge-cloud Collaborative Learning with Federated and Centralized Features Z Li*, Q Li*, Y Zhou, W Zhong, G Zhang, C Wu Proceedings of the 46th International ACM SIGIR Conference on Research and …, 2023 | 12 | 2023 |
| An early assessment of the County Medical Community reform in China: a case study of Zhejiang province C Wu, Y Tu, Z Li, J Yu Journal of Chinese Governance 6 (4), 463-485, 2021 | 12 | 2021 |
| Learning Cautiously in Federated Learning with Noisy and Heterogeneous Clients C Wu*, Z Li*, F Wang, C Wu 2023 IEEE International Conference on Multimedia and Expo (ICME 2023), 2023 | 11 | 2023 |
| Neural Collapse Anchored Prompt Tuning for Generalizable Vision-Language Models D Zhu, Z Li, M Zhang, J Yuan, Y Shao, J Liu, K Kuang, Y Li, C Wu KDD 2024, 0 | 11* | |
| Ensemble Federated Adversarial Training with Non-IID data S Luo, D Zhu, Z Li, C Wu FTL-IJCAI 2021, 2021 | 8 | 2021 |
| Scalable Geometric Fracture Assembly via Co-creation Space among Assemblers R Zhang, J Liu, Z Li, H Dong, J Fu, C Wu AAAI 2024, 2023 | 6 | 2023 |
| FediOS: Decoupling Orthogonal Subspaces for Personalization in Feature-skew Federated Learning L Gao*, Z Li*, Y Lu, C Wu arXiv preprint arXiv:2311.18559, 2023 | 5 | 2023 |
| Training-time neuron alignment through permutation subspace for improving linear mode connectivity and model fusion Z Li, Z Li, J Lin, T Shen, T Lin, C Wu arXiv preprint arXiv:2402.01342, 2024 | 4 | 2024 |
| 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 ICLR 2025, 2024 | 3 | 2024 |
| Text-to-model: Text-conditioned neural network diffusion for train-once-for-all personalization Z Li, L Gao, C Wu arXiv preprint arXiv:2405.14132, 2024 | 3 | 2024 |
| Photon: Federated LLM Pre-Training L Sani, A Iacob, Z Cao, R Lee, B Marino, Y Gao, D Cai, Z Li, W Zhao, ... MLSys 2025, 2024 | 1 | 2024 |
chao wuZhejiang UniversityEmail verificata su zju.edu.cn