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cs.DC2026
When Is Shallow Enough? Adaptive Split Federated Learning with Client-Specific Sufficiency Estimation
Wenhao Yuan, Chenchen Lin, Wentao Hu +4
\textit{Split Federated Learning} (SFL) enables distributed model training by splitting networks between the server and clients. However, under client heterogeneity, the convention…
cs.DC2026
From Cloud to Crowd: Democratizing LLM Service with Decentralized Edge Collaboration for RAG
Jiaxing Li, Hengzhi Wang, Feng Wang +5
The rapid advancement of large language models (LLMs) has increased demand for scalable and cost-effective deployment, especially for mobile and edge devices. Cloud-hosted LLMs are…