Zexi Li

According to our database, Zexi Li authored at least 26 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Toward Universal Personalization in Federated Learning via Collaborative Foundation Generative Models.

Chenrui Wu, Zexi Li, Fangxin Wang, Hongyang Chen, Jiajun Bu, Haishuai Wang

IEEE Trans. Mob. Comput., October, 2025

FediOS: decoupling orthogonal subspaces for personalization in feature-skew federated learning.

Lingzhi Gao, Zexi Li, Xinyi Shang, Yang Lu, Chao Wu

Mach. Learn., October, 2025

FedMcon: an adaptive aggregation method for federated learning via meta controller.

Tao Shen, Zexi Li, Ziyu Zhao, Didi Zhu, Zheqi Lv, Kun Kuang, Shengyu Zhang, Chao Wu, Fei Wu

Frontiers Inf. Technol. Electron. Eng., August, 2025

FedEve: On Bridging the Client Drift and Period Drift for Cross-device Federated Learning.

Tao Shen, Zexi Li, Didi Zhu, Ziyu Zhao, Chao Wu, Fei Wu

CoRR, August, 2025

You Are Your Own Best Teacher: Achieving Centralized-level Performance in Federated Learning under Heterogeneous and Long-tailed Data.

Shanshan Yan, Zexi Li, Chao Wu, Meng Pang, Yang Lu, Yan Yan, Hanzi Wang

CoRR, March, 2025

Merging LoRAs like Playing LEGO: Pushing the Modularity of LoRA to Extremes Through Rank-Wise Clustering.

Ziyu Zhao, Tao Shen, Didi Zhu, Zexi Li, Jing Su, Xuwu Wang, Fei Wu

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Towards Effective Clustered Federated Learning: A Peer-to-Peer Framework With Adaptive Neighbor Matching.

Zexi Li, Jiaxun Lu, Shuang Luo, Didi Zhu, Yunfeng Shao, Yinchuan Li, Zhimeng Zhang, Yongheng Wang, Chao Wu

IEEE Trans. Big Data, December, 2024

Merging LoRAs like Playing LEGO: Pushing the Modularity of LoRA to Extremes Through Rank-Wise Clustering.

Ziyu Zhao, Tao Shen, Didi Zhu, Zexi Li, Jing Su, Xuwu Wang, Kun Kuang, Fei Wu

CoRR, 2024

Text-to-Model: Text-Conditioned Neural Network Diffusion for Train-Once-for-All Personalization.

Zexi Li, Lingzhi Gao, Chao Wu

CoRR, 2024

Improving Group Connectivity for Generalization of Federated Deep Learning.

Zexi Li, Jie Lin, Zhiqi Li, Didi Zhu, Chao Wu

CoRR, 2024

Training-time Neuron Alignment through Permutation Subspace for Improving Linear Mode Connectivity and Model Fusion.

Zexi Li, Zhiqi Li, Jie Lin, Tao Shen, Tao Lin, Chao Wu

CoRR, 2024

Neural Collapse Anchored Prompt Tuning for Generalizable Vision-Language Models.

Didi Zhu, Zexi Li, Min Zhang, Junkun Yuan, Jiashuo Liu, Kun Kuang, Chao Wu

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models.

Didi Zhu, Zhongyi Sun, Zexi Li, Tao Shen, Ke Yan, Shouhong Ding, Chao Wu, Kun Kuang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Scalable Geometric Fracture Assembly via Co-creation Space among Assemblers.

Ruiyuan Zhang, Jiaxiang Liu, Zexi Li, Hao Dong, Jie Fu, Chao Wu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

FediOS: Decoupling Orthogonal Subspaces for Personalization in Feature-skew Federated Learning.

Lingzhi Gao, Zexi Li, Yang Lu, Chao Wu

CoRR, 2023

Bridging the Gap: Neural Collapse Inspired Prompt Tuning for Generalization under Class Imbalance.

Didi Zhu, Yinchuan Li, Min Zhang, Junkun Yuan, Jiashuo Liu, Zexi Li, Kun Kuang, Chao Wu

CoRR, 2023

Universal Domain Adaptation via Compressive Attention Matching.

Didi Zhu, Yinchuan Li, Junkun Yuan, Zexi Li, Yunfeng Shao, Kun Kuang, Chao Wu

CoRR, 2023

Edge-cloud Collaborative Learning with Federated and Centralized Features.

Zexi Li, Qunwei Li, Yi Zhou, Wenliang Zhong, Guannan Zhang, Chao Wu

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Revisiting Weighted Aggregation in Federated Learning with Neural Networks.

Zexi Li, Tao Lin, Xinyi Shang, Chao Wu

Proceedings of the International Conference on Machine Learning, 2023

Learning Cautiously in Federated Learning with Noisy and Heterogeneous Clients.

Chenrui Wu, Zexi Li, Fangxin Wang, Chao Wu

Proceedings of the IEEE International Conference on Multimedia and Expo, 2023

Universal Domain Adaptation via Compressive Attention Matching.

Didi Zhu, Yinchuan Li, Junkun Yuan, Zexi Li, Kun Kuang, Chao Wu

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier.

Zexi Li, Xinyi Shang, Rui He, Tao Lin, Chao Wu

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

Can we share models if sharing data is not an option?

Zexi Li, Feng Mao, Chao Wu

Patterns, 2022

Mining Latent Relationships among Clients: Peer-to-peer Federated Learning with Adaptive Neighbor Matching.

Zexi Li, Jiaxun Lu, Shuang Luo, Didi Zhu, Yunfeng Shao, Yinchuan Li, Zhimeng Zhang, Chao Wu

CoRR, 2022

2021

Ensemble Federated Adversarial Training with Non-IID data.

Shuang Luo, Didi Zhu, Zexi Li, Chao Wu

CoRR, 2021

Boosting the generalization ability of Vis-NIR-spectroscopy-based regression models through dimension reduction and transfer learning.

Xiaoli Li, Zexi Li, Xufeng Yang, Yong He

Comput. Electron. Agric., 2021