2 papers
cs.LG2025
FedLoRA-Optimizer: Federated LoRA Fine-Tuning with Global and Local Optimization in Heterogeneous Data Scenarios
Jianzhe Zhao, Hailin Zhu, Yu Zhang +2
Federated efficient fine-tuning has emerged as an approach that leverages distributed data and computational resources across nodes to address the challenges of large-scale fine-tu…
cs.LG2025
FedEPA: Enhancing Personalization and Modality Alignment in Multimodal Federated Learning
Yu Zhang, Qingfeng Du, Jiaqi Lv
Federated Learning (FL) enables decentralized model training across multiple parties while preserving privacy. However, most FL systems assume clients hold only unimodal data, limi…