Zhikang Shen

SDFLoRA: Selective Decoupled Federated LoRA for Privacy-preserving Fine-tuning with Heterogeneous Clients

Federated learning (FL) has emerged as a promising paradigm for adapting large language models (LLMs) to distributed data. To mitigate the high communication and memory overhead, parameter efficient techniques such as Low Rank Adaptation (LoRA) are widely adopted. However, practical deployments ofte