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cs.CV2025
FedBM: Stealing Knowledge from Pre-trained Language Models for Heterogeneous Federated Learning
Meilu Zhu, Qiushi Yang, Zhifan Gao +2
Federated learning (FL) has shown great potential in medical image computing since it provides a decentralized learning paradigm that allows multiple clients to train a model colla…
cs.CV2024
DEeR: Deviation Eliminating and Noise Regulating for Privacy-preserving Federated Low-rank Adaptation
Meilu Zhu, Axiu Mao, Jun Liu +1
Integrating low-rank adaptation (LoRA) with federated learning (FL) has received widespread attention recently, aiming to adapt pretrained foundation models (FMs) to downstream med…