Zhuzhong Qian

Optimizing Cross-Client Domain Coverage for Federated Instruction Tuning of Large Language Models

Federated domain-specific instruction tuning (FedDIT) for large language models (LLMs) aims to enhance performance in specialized domains using distributed private and limited data, yet identifying key performance drivers and optimal augmentation strategies remains challenging. We empirically establ