Federated Mutual Learning. - Tao Shen 002; Jie Zhang 081; Xinkang Jia; Fengda Zhang; Gang Huang 004; Pan Zhou; Fei Wu 001; Chao Wu 001 (CoRR, 2020)

Federated Unsupervised Representation Learning. - Fengda Zhang; Kun Kuang; Zhaoyang You; Tao Shen 002; Jun Xiao 001; Yin Zhang 006; Chao Wu 001; Yueting Zhuang; Xiaolin Li (CoRR, 2020)

Federated Graph Learning - A Position Paper. - Huanding Zhang; Tao Shen 002; Fei Wu 001; Mingyang Yin; Hongxia Yang; Chao Wu 001 (CoRR, 2021)

Edge-Cloud Polarization and Collaboration: A Comprehensive Survey. - Jiangchao Yao; Shengyu Zhang 001; Yang Yao; Feng Wang 072; Jianxin Ma; Jianwei Zhang 012; Yunfei Chu; Luo Ji; Kunyang Jia; Tao Shen 002; Anpeng Wu; Fengda Zhang; et al. (CoRR, 2021)

MetaNetwork: A Task-agnostic Network Parameters Generation Framework for Improving Device Model Generalization. - Zheqi Lv; Feng Wang 072; Kun Kuang; Yongwei Wang; Zhengyu Chen 001; Tao Shen 002; Hongxia Yang; Fei Wu 001 (CoRR, 2022)

DUET: A Tuning-Free Device-Cloud Collaborative Parameters Generation Framework for Efficient Device Model Generalization. - Zheqi Lv; Wenqiao Zhang; Shengyu Zhang 001; Kun Kuang; Feng Wang 072; Yongwei Wang; Zhengyu Chen 001; Tao Shen 002; Hongxia Yang; Beng Chin Ooi; Fei Wu 001 (WWW, 2023)

Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AI. - Jiangchao Yao; Shengyu Zhang 001; Yang Yao; Feng Wang 072; Jianxin Ma; Jianwei Zhang 012; Yunfei Chu; Luo Ji; Kunyang Jia; Tao Shen 002; Anpeng Wu; Fengda Zhang; et al. (IEEE Trans. Knowl. Data Eng., 2023)

Federated unsupervised representation learning. - Fengda Zhang; Kun Kuang; Long Chen 016; Zhaoyang You; Tao Shen 002; Jun Xiao 001; Yin Zhang 006; Chao Wu 001; Fei Wu 001; Yueting Zhuang; Xiaolin Li (Frontiers Inf. Technol. Electron. Eng., 2023)

Federated mutual learning: a collaborative machine learning method for heterogeneous data, models, and objectives. - Tao Shen 002; Jie Zhang 081; Xinkang Jia; Fengda Zhang; Zheqi Lv; Kun Kuang; Chao Wu 001; Fei Wu 001 (Frontiers Inf. Technol. Electron. Eng., 2023)

Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models. - Didi Zhu; Zhongyi Sun 002; Zexi Li 001; Tao Shen 002; Ke Yan; Shouhong Ding; Chao Wu 001; Kun Kuang (ICML, 2024)

Training-time Neuron Alignment through Permutation Subspace for Improving Linear Mode Connectivity and Model Fusion. - Zexi Li 001; Zhiqi Li 004; Jie Lin; Tao Shen 002; Tao Lin; Chao Wu 001 (CoRR, 2024)

Retrieval-Augmented Mixture of LoRA Experts for Uploadable Machine Learning. - Ziyu Zhao 001; Leilei Gan; Guoyin Wang 002; Yuwei Hu; Tao Shen 002; Hongxia Yang; Kun Kuang; Fei Wu 001 (CoRR, 2024)

Merging LoRAs like Playing LEGO: Pushing the Modularity of LoRA to Extremes Through Rank-Wise Clustering. - Ziyu Zhao 001; Tao Shen 002; Didi Zhu; Zexi Li 001; Jing Su; Xuwu Wang; Kun Kuang; Fei Wu 001 (CoRR, 2024)

Deconfounded hierarchical multi-granularity classification. - Ziyu Zhao 001; Leilei Gan; Tao Shen 002; Kun Kuang; Fei Wu 001 (Comput. Vis. Image Underst., 2024)

FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning. - Zhonghua Jiang 007; Jimin Xu; Shengyu Zhang 001; Tao Shen 002; Jiwei Li 001; Kun Kuang; Haibin Cai; Fei Wu 001 (AAAI, 2025)

Merging LoRAs like Playing LEGO: Pushing the Modularity of LoRA to Extremes Through Rank-Wise Clustering. - Ziyu Zhao 001; Tao Shen 002; Didi Zhu; Zexi Li 001; Jing Su; Xuwu Wang; Fei Wu 001 (ICLR, 2025)

REMEDY: Recipe Merging Dynamics in Large Vision-Language Models. - Didi Zhu; Yibing Song; Tao Shen 002; Ziyu Zhao 001; Jinluan Yang; Min Zhang 005; Chao Wu 001 (ICLR, 2025)

Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-Task Learning. - Ziyu Zhao 001; Yixiao Zhou; Didi Zhu; Tao Shen 002; Xuwu Wang; Jing Su; Kun Kuang; Zhongyu Wei; Fei Wu 001; Yu Cheng (CoRR, 2025)

Will LLMs Scaling Hit the Wall? Breaking Barriers via Distributed Resources on Massive Edge Devices. - Tao Shen 002; Didi Zhu; Ziyu Zhao 001; Chao Wu 001; Fei Wu 001 (CoRR, 2025)