Didi Zhu

According to our database, Didi Zhu authored at least 14 papers between 2021 and 2024.

Collaborative distances:

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

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

Mitigating the Backdoor Effect for Multi-Task Model Merging via Safety-Aware Subspace.

Jinluan Yang, Anke Tang, Didi Zhu, Zhengyu Chen, Li Shen, Fei Wu

CoRR, 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

Improving Group Connectivity for Generalization of Federated Deep Learning.

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

CoRR, 2024

RESMatch: Referring Expression Segmentation in a Semi-Supervised Manner.

Ying Zang, Chenglong Fu, Runlong Cao, Didi Zhu, Min Zhang, Wenjun Hu, Lanyun Zhu, Tianrun Chen

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

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

Generalized Universal Domain Adaptation with Generative Flow Networks.

Didi Zhu, Yinchuan Li, Yunfeng Shao, Jianye Hao, Fei Wu, Kun Kuang, Jun Xiao, Chao Wu

Proceedings of the 31st ACM International Conference on Multimedia, 2023

Quantitatively Measuring and Contrastively Exploring Heterogeneity for Domain Generalization.

Yunze Tong, Junkun Yuan, Min Zhang, Didi Zhu, Keli Zhang, Fei Wu, Kun Kuang

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 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

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