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cs.DC2026
Three Birds, One Stone: Solving the Communication-Memory-Privacy Trilemma in LLM Fine-tuning Over Wireless Networks with Zeroth-Order Optimization
Zhijie Cai, Yuhao Zheng, Haolong Chen +3
Federated Learning (FL) offers a promising pathway for collaboratively fine-tuning Large Language Models (LLMs) at the edge; however, this paradigm faces a critical bottleneck: the…
cs.DC2025
Communication-and-Computation Efficient Split Federated Learning: Gradient Aggregation and Resource Management
Yipeng Liang, Qimei Chen, Guangxu Zhu +2
With the prevalence of Large Learning Models (LLM), Split Federated Learning (SFL), which divides a learning model into server-side and client-side models, has emerged as an appeal…