Tao Shen

According to our database, Tao Shen authored at least 23 papers between 2020 and 2025.

Collaborative distances:

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

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

FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models.

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

CoRR, June, 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

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

FedGuCci: Making Local Models More Connected in Landscape for Federated Learning.

Zexi Li, Jie Lin, Zhiqi Li, Didi Zhu, Tao Shen, Tao Lin, Chao Wu, Nicholas D. Lane

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 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

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

FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning.

Zhonghua Jiang, Jimin Xu, Shengyu Zhang, Tao Shen, Jiwei Li, Kun Kuang, Haibin Cai, Fei Wu

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Deconfounded hierarchical multi-granularity classification.

Ziyu Zhao, Leilei Gan, Tao Shen, Kun Kuang, Fei Wu

Comput. Vis. Image Underst., 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

Retrieval-Augmented Mixture of LoRA Experts for Uploadable Machine Learning.

Ziyu Zhao, Leilei Gan, Guoyin Wang, Yuwei Hu, Tao Shen, Hongxia Yang, Kun Kuang, Fei 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

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

Federated mutual learning: a collaborative machine learning method for heterogeneous data, models, and objectives.

Tao Shen, Jie Zhang, Xinkang Jia, Fengda Zhang, Zheqi Lv, Kun Kuang, Chao Wu, Fei Wu

Frontiers Inf. Technol. Electron. Eng., October, 2023

Federated unsupervised representation learning.

Fengda Zhang, Kun Kuang, Long Chen, Zhaoyang You, Tao Shen, Jun Xiao, Yin Zhang, Chao Wu, Fei Wu, Yueting Zhuang, Xiaolin Li

Frontiers Inf. Technol. Electron. Eng., August, 2023

Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AI.

Jiangchao Yao, Shengyu Zhang, Yang Yao, Feng Wang, Jianxin Ma, Jianwei Zhang, Yunfei Chu, Luo Ji, Kunyang Jia, Tao Shen, Anpeng Wu, Fengda Zhang, Ziqi Tan, Kun Kuang, Chao Wu, Fei Wu, Jingren Zhou, Hongxia Yang

IEEE Trans. Knowl. Data Eng., July, 2023

DUET: A Tuning-Free Device-Cloud Collaborative Parameters Generation Framework for Efficient Device Model Generalization.

Zheqi Lv, Wenqiao Zhang, Shengyu Zhang, Kun Kuang, Feng Wang, Yongwei Wang, Zhengyu Chen, Tao Shen, Hongxia Yang, Beng Chin Ooi, Fei Wu

Proceedings of the ACM Web Conference 2023, 2023

2022

MetaNetwork: A Task-agnostic Network Parameters Generation Framework for Improving Device Model Generalization.

Zheqi Lv, Feng Wang, Kun Kuang, Yongwei Wang, Zhengyu Chen, Tao Shen, Hongxia Yang, Fei Wu

CoRR, 2022

2021

Edge-Cloud Polarization and Collaboration: A Comprehensive Survey.

Jiangchao Yao, Shengyu Zhang, Yang Yao, Feng Wang, Jianxin Ma, Jianwei Zhang, Yunfei Chu, Luo Ji, Kunyang Jia, Tao Shen, Anpeng Wu, Fengda Zhang, Ziqi Tan, Kun Kuang, Chao Wu, Fei Wu, Jingren Zhou, Hongxia Yang

CoRR, 2021

Federated Graph Learning - A Position Paper.

Huanding Zhang, Tao Shen, Fei Wu, Mingyang Yin, Hongxia Yang, Chao Wu

CoRR, 2021

2020

Federated Unsupervised Representation Learning.

Fengda Zhang, Kun Kuang, Zhaoyang You, Tao Shen, Jun Xiao, Yin Zhang, Chao Wu, Yueting Zhuang, Xiaolin Li

CoRR, 2020

Federated Mutual Learning.

Tao Shen, Jie Zhang, Xinkang Jia, Fengda Zhang, Gang Huang, Pan Zhou, Fei Wu, Chao Wu

CoRR, 2020