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ORCIDZexi Li 0001
Person information
- affiliation: Zhejiang University, College of Computer Science and Technology, Hangzhou, China
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- Zexi Li — disambiguation page
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2020 – today
- 2026
[j7]Zexi Li
, Zhiqi Li, Jie Lin, Tao Shen, Jun Xiao, Yike Guo, Tao Lin, Chao Wu:
Improving Model Fusion by Training-Time Neuron Alignment With Fixed Neuron Anchors. IEEE Trans. Pattern Anal. Mach. Intell. 48(3): 2186-2199 (2026)- 2025
- [j6]Tao Shen, Zexi Li, Ziyu Zhao, Didi Zhu, Zheqi Lv, Kun Kuang, Shengyu Zhang, Chao Wu, Fei Wu:
FedMcon: an adaptive aggregation method for federated learning via meta controller. Frontiers Inf. Technol. Electron. Eng. 26(8): 1378-1393 (2025) - [j5]Lingzhi Gao, Zexi Li, Xinyi Shang, Yang Lu, Chao Wu:
FediOS: decoupling orthogonal subspaces for personalization in feature-skew federated learning. Mach. Learn. 114(10): 228 (2025) - [j4]Chenrui Wu, Zexi Li, Fangxin Wang, Hongyang Chen, Jiajun Bu, Haishuai Wang:
Toward Universal Personalization in Federated Learning via Collaborative Foundation Generative Models. IEEE Trans. Mob. Comput. 24(10): 9695-9708 (2025) - [c13]Ziyu Zhao, Tao Shen, Didi Zhu, Zexi Li, Jing Su, Xuwu Wang, Fei Wu:
Merging LoRAs like Playing LEGO: Pushing the Modularity of LoRA to Extremes Through Rank-Wise Clustering. ICLR 2025 - [c12]Zexi Li, Jie Lin, Zhiqi Li, Didi Zhu, Tao Shen, Tao Lin, Chao Wu, Nicholas D. Lane:
FedGuCci: Making Local Models More Connected in Landscape for Federated Learning. KDD (2) 2025: 1659-1670 - [c11]Lorenzo Sani, Alex Iacob, Zeyu Cao, Royson Lee, Bill Marino, Yan Gao, Wanru Zhao, Dongqi Cai, Zexi Li, Xinchi Qiu, Nicholas D. Lane:
Photon: Federated LLM Pre-Training. MLSys 2025 - [c10]Bowen Tian, Wenshuo Chen, Zexi Li, Songning Lai, Jiemin Wu, Yutao Yue:
Text2Weight: Bridging Natural Language and Neural Network Weight Spaces. ACM Multimedia 2025: 10152-10160 - [i22]Shanshan Yan, Zexi Li, Chao Wu, Meng Pang, Yang Lu, Yan Yan, Hanzi Wang:
You Are Your Own Best Teacher: Achieving Centralized-level Performance in Federated Learning under Heterogeneous and Long-tailed Data. CoRR abs/2503.06916 (2025) - [i21]Zexi Li, Xiangzhu Wang, William F. Shen, Meghdad Kurmanji, Xinchi Qiu, Dongqi Cai, Chao Wu, Nicholas D. Lane:
Editing as Unlearning: Are Knowledge Editing Methods Strong Baselines for Large Language Model Unlearning? CoRR abs/2505.19855 (2025) - [i20]Yan Gao, Massimo Roberto Scamarcia, Javier Fernández-Marqués, Mohammad Naseri, Chong Shen Ng, Dimitris Stripelis, Zexi Li, Tao Shen, Jiamu Bai, Daoyuan Chen, Zikai Zhang, Rui Hu, Inseo Song, Lee KangYoon, Hong Jia, Ting Dang, Junyan Wang, Zheyuan Liu, Daniel J. Beutel, Lingjuan Lyu, Nicholas D. Lane:
FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models. CoRR abs/2506.02961 (2025) - [i19]Zhenyan Lu, Daliang Xu, Dongqi Cai, Zexi Li, Wei Liu, Fangming Liu, Shangguang Wang, Mengwei Xu:
MobiEdit: Resource-efficient Knowledge Editing for Personalized On-device LLMs. CoRR abs/2506.13772 (2025) - [i18]Bowen Tian, Wenshuo Chen, Zexi Li, Songning Lai, Jiemin Wu, Yutao Yue:
Text2Weight: Bridging Natural Language and Neural Network Weight Spaces. CoRR abs/2508.13633 (2025) - [i17]Tao Shen, Zexi Li, Didi Zhu, Ziyu Zhao, Chao Wu, Fei Wu:
FedEve: On Bridging the Client Drift and Period Drift for Cross-device Federated Learning. CoRR abs/2508.14539 (2025) - 2024
- [j3]Zexi Li, Jiaxun Lu, Shuang Luo, Didi Zhu, Yunfeng Shao, Yinchuan Li, Zhimeng Zhang, Yongheng Wang, Chao Wu:
Towards Effective Clustered Federated Learning: A Peer-to-Peer Framework With Adaptive Neighbor Matching. IEEE Trans. Big Data 10(6): 812-826 (2024) - [c9]Ruiyuan Zhang, Jiaxiang Liu, Zexi Li, Hao Dong, Jie Fu, Chao Wu:
Scalable Geometric Fracture Assembly via Co-creation Space among Assemblers. AAAI 2024: 7269-7277 - [c8]Didi Zhu, Zhongyi Sun, Zexi Li, Tao Shen, Ke Yan, Shouhong Ding, Chao Wu, Kun Kuang:
Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models. ICML 2024: 62581-62598 - [c7]Didi Zhu, Zexi Li, Min Zhang, Junkun Yuan, Jiashuo Liu, Kun Kuang, Chao Wu:
Neural Collapse Anchored Prompt Tuning for Generalizable Vision-Language Models. KDD 2024: 4631-4640 - [c6]Tao Shen, Zexi Li, Ziyu Zhao, Didi Zhu, Zheqi Lv, Shengyu Zhang, Kun Kuang, Fei Wu:
An Adaptive Aggregation Method for Federated Learning via Meta Controller. MMAsia Workshops 2024: 20:1 - [i16]Zexi Li, Zhiqi Li, Jie Lin, Tao Shen, Tao Lin, Chao Wu:
Training-time Neuron Alignment through Permutation Subspace for Improving Linear Mode Connectivity and Model Fusion. CoRR abs/2402.01342 (2024) - [i15]Didi Zhu, Zhongyi Sun, Zexi Li, Tao Shen, Ke Yan, Shouhong Ding, Kun Kuang, Chao Wu:
Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models. CoRR abs/2402.12048 (2024) - [i14]Zexi Li, Jie Lin, Zhiqi Li, Didi Zhu, Chao Wu:
Improving Group Connectivity for Generalization of Federated Deep Learning. CoRR abs/2402.18949 (2024) - [i13]Zexi Li, Lingzhi Gao, Chao Wu:
Text-to-Model: Text-Conditioned Neural Network Diffusion for Train-Once-for-All Personalization. CoRR abs/2405.14132 (2024) - [i12]Ziyu Zhao, Tao Shen, Didi Zhu, Zexi Li, Jing Su, Xuwu Wang, Kun Kuang, Fei Wu:
Merging LoRAs like Playing LEGO: Pushing the Modularity of LoRA to Extremes Through Rank-Wise Clustering. CoRR abs/2409.16167 (2024) - [i11]Lorenzo Sani, Alex Iacob, Zeyu Cao, Royson Lee, Bill Marino, Yan Gao, Dongqi Cai, Zexi Li, Wanru Zhao, Xinchi Qiu, Nicholas D. Lane:
Photon: Federated LLM Pre-Training. CoRR abs/2411.02908 (2024) - 2023
- [c5]Zexi Li, Xinyi Shang, Rui He, Tao Lin, Chao Wu:
No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier. ICCV 2023: 5296-5306 - [c4]Didi Zhu, Yinchuan Li, Junkun Yuan, Zexi Li, Kun Kuang, Chao Wu:
Universal Domain Adaptation via Compressive Attention Matching. ICCV 2023: 6951-6962 - [c3]Chenrui Wu, Zexi Li, Fangxin Wang, Chao Wu:
Learning Cautiously in Federated Learning with Noisy and Heterogeneous Clients. ICME 2023: 660-665 - [c2]Zexi Li, Tao Lin, Xinyi Shang, Chao Wu:
Revisiting Weighted Aggregation in Federated Learning with Neural Networks. ICML 2023: 19767-19788 - [c1]Zexi Li, Qunwei Li, Yi Zhou, Wenliang Zhong, Guannan Zhang, Chao Wu:
Edge-cloud Collaborative Learning with Federated and Centralized Features. SIGIR 2023: 1949-1953 - [i10]Zexi Li, Tao Lin, Xinyi Shang, Chao Wu:
Revisiting Weighted Aggregation in Federated Learning with Neural Networks. CoRR abs/2302.10911 (2023) - [i9]Zexi Li, Xinyi Shang, Rui He, Tao Lin, Chao Wu:
No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier. CoRR abs/2303.10058 (2023) - [i8]Chenrui Wu, Zexi Li, Fangxin Wang, Chao Wu:
Learning Cautiously in Federated Learning with Noisy and Heterogeneous Clients. CoRR abs/2304.02892 (2023) - [i7]Zexi Li, Qunwei Li, Yi Zhou, Wenliang Zhong, Guannan Zhang, Chao Wu:
Edge-cloud Collaborative Learning with Federated and Centralized Features. CoRR abs/2304.05871 (2023) - [i6]Didi Zhu, Yinchuan Li, Junkun Yuan, Zexi Li, Yunfeng Shao, Kun Kuang, Chao Wu:
Universal Domain Adaptation via Compressive Attention Matching. CoRR abs/2304.11862 (2023) - [i5]Didi Zhu, Yinchuan Li, Min Zhang, Junkun Yuan, Jiashuo Liu, Zexi Li, Kun Kuang, Chao Wu:
Bridging the Gap: Neural Collapse Inspired Prompt Tuning for Generalization under Class Imbalance. CoRR abs/2306.15955 (2023) - [i4]Lingzhi Gao, Zexi Li, Yang Lu, Chao Wu:
FediOS: Decoupling Orthogonal Subspaces for Personalization in Feature-skew Federated Learning. CoRR abs/2311.18559 (2023) - [i3]Ruiyuan Zhang, Jiaxiang Liu, Zexi Li, Hao Dong, Jie Fu, Chao Wu:
Scalable Geometric Fracture Assembly via Co-creation Space among Assemblers. CoRR abs/2312.12340 (2023) - 2022
- [j2]Zexi Li, Feng Mao, Chao Wu:
Can we share models if sharing data is not an option? Patterns 3(11): 100603 (2022) - [i2]Zexi Li, Jiaxun Lu, Shuang Luo, Didi Zhu, Yunfeng Shao, Yinchuan Li, Zhimeng Zhang, Chao Wu:
Mining Latent Relationships among Clients: Peer-to-peer Federated Learning with Adaptive Neighbor Matching. CoRR abs/2203.12285 (2022) - 2021
- [j1]Xiaoli Li, Zexi Li, Xufeng Yang, Yong He:
Boosting the generalization ability of Vis-NIR-spectroscopy-based regression models through dimension reduction and transfer learning. Comput. Electron. Agric. 186: 106157 (2021) - [i1]Shuang Luo, Didi Zhu, Zexi Li, Chao Wu:
Ensemble Federated Adversarial Training with Non-IID data. CoRR abs/2110.14814 (2021)
Coauthor Index
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