AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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L-shaped SFT is presented, a split fine-tuning framework that removes the need for continuous client participation and introduces one-shot SFT, in which clients upload activations once and then go offline while the server continues optimization over cached representations.
FlexP-SFT is proposed, a novel aggregation-free framework for personalized split federated fine-tuning, which fundamentally eliminates the client-side aggregation process and introduces a layer-flexible alignment strategy to balance personalization and generalization capabilities.
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