2 papers
cs.DC2025
Flexible Personalized Split Federated Learning for On-Device Fine-Tuning of Foundation Models
Tianjun Yuan, Jiaxiang Geng, Pengchao Han +2
Fine-tuning foundation models is critical for superior performance on personalized downstream tasks, compared to using pre-trained models. Collaborative learning can leverage local…
cs.LG2025
Adaptive Federated LoRA in Heterogeneous Wireless Networks with Independent Sampling
Yanzhao Hou, Jiaxiang Geng, Boyu Li +4
Federated LoRA has emerged as a promising technique for efficiently fine-tuning large language models (LLMs) on distributed devices by reducing the number of trainable parameters.…