2 papers
cs.CL2026
FedMosaic: Federated Retrieval-Augmented Generation via Parametric Adapters
Zhilin Liang, Yuxiang Wang, Zimu Zhou +3
Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by grounding generation in external knowledge to improve factuality and reduce hallucinations. Yet most d…
cs.LG2026
Federated Personalization of Early-Exit Networks
Boyi Liu, Zimu Zhou, Cheng Fang +1
Personalized Federated Learning (PFL) excels at tailoring client-specific models, which is particularly critical for decentralized and heterogeneous data environments, yet existing…