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Federated Learning for LLMs over Mobile Networks: Issues and Solutions in the RAN Transport
Federated LLM fine-tuning enables large models to be adapted using private and geographically distributed data at the network edge, creating recurring and deadline-sensitive communication workloads across access and transport networks. This challenge is particularly relevant in mobile RANs, where wi
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