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Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Author

Yuqing Li

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Book Open access Aug 2026

Efficient and Differentially Private Federated LLM Fine-Tuning on Heterogeneous Clients

Federated low-rank adaptation (FedLoRA) allows multiple clients to collaboratively fine-tune large language models (LLMs) on downstream tasks without exposing their private data. To mitigate privacy leakage during aggregation, differential privacy (DP) is widely used to clip and perturb local model updates with noise,...

Nan Yan, Yu-Qing Li, Xiong Wang et al. · 0 citations
Book Open access Aug 2026

Efficient and Differentially Private Federated LLM Fine-Tuning on Heterogeneous Clients

i-FedLoRA provides privacy guarantees, improves model accuracy by up to 3.8%, and expedites training by 1.37-2.23×, and facilitates heterogeneous LoRA aggregation that selectively prioritizes high-confidence knowledge to filter DP-induced noise, thereby achieving robust knowledge transfer.

Nan Yan, Yuqing Li, Xiong Wang et al. · 0 citations

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