2026
Heterogeneous Customizable Personalized Federated Fine-Tuning Approach for Large Language Models
ICML 2026poster
Personalized federated LoRA fine tuning has become a key approach to addressing data heterogeneity in distributed fine tuning of large language models (LLMs). Existing methods typically assume homogeneous personalization needs across clients, relying on dual LoRA or personalized calibration schemes.…