Didi Zhu

According to our database, Didi Zhu authored at least 26 papers between 2021 and 2025.

Collaborative distances:

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

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

Will LLMs Scaling Hit the Wall? Breaking Barriers via Distributed Resources on Massive Edge Devices.

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

CoRR, March, 2025

Keeping Yourself is Important in Downstream Tuning Multimodal Large Language Model.

Wenke Huang, Jian Liang, Xianda Guo, Yiyang Fang, Guancheng Wan, Xuankun Rong, Chi Wen, Zekun Shi, Qingyun Li, Didi Zhu, Yanbiao Ma, Ke Liang, Bin Yang, He Li, Jiawei Shao, Mang Ye, Bo Du

CoRR, March, 2025

Generative Artificial Intelligence in Robotic Manipulation: A Survey.

Kun Zhang, Peng Yun, Jun Cen, Junhao Cai, Didi Zhu, Hangjie Yuan, Chao Zhao, Tao Feng, Michael Yu Wang, Qifeng Chen, Jia Pan, Wei Zhang, Bo Yang, Hua Chen

CoRR, March, 2025

Mix Data or Merge Models? Balancing the Helpfulness, Honesty, and Harmlessness of Large Language Model via Model Merging.

Jinluan Yang, Dingnan Jin, Anke Tang, Li Shen, Didi Zhu, Zhengyu Chen, Daixin Wang, Qing Cui, Zhiqiang Zhang, Jun Zhou, Fei Wu, Kun Kuang

CoRR, February, 2025

Let Human Sketches Help: Empowering Challenging Image Segmentation Task with Freehand Sketches.

Ying Zang, Runlong Cao, Jianqi Zhang, Yidong Han, Ziyue Cao, Wenjun Hu, Didi Zhu, Lanyun Zhu, Zejian Li, Deyi Ji, Tianrun Chen

CoRR, January, 2025

Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-Task Learning.

Ziyu Zhao, Yixiao Zhou, Didi Zhu, Tao Shen, Xuwu Wang, Jing Su, Kun Kuang, Zhongyu Wei, Fei Wu, Yu Cheng

CoRR, January, 2025

ZeroFlow: Overcoming Catastrophic Forgetting is Easier than You Think.

Tao Feng, Wei Li, Didi Zhu, Hangjie Yuan, Wendi Zheng, Dan Zhang, Jie Tang

CoRR, January, 2025

REMEDY: Recipe Merging Dynamics in Large Vision-Language Models.

Didi Zhu, Yibing Song, Tao Shen, Ziyu Zhao, Jinluan Yang, Min Zhang, Chao Wu

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

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

Proceedings of the Thirteenth International Conference on Learning Representations, 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

Learn from Downstream and Be Yourself in Multimodal Large Language Model Fine-Tuning.

Wenke Huang, Jian Liang, Zekun Shi, Didi Zhu, Guancheng Wan, He Li, Bo Du, Dacheng Tao, Mang Ye

CoRR, 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