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A Split-and-Privatize Framework for Large Language Model Fine-Tuning
Fine-tuning is a prominent technique to adapt a pre-trained language model to downstream scenarios.
Secure Split Learning against Property Inference, Data Reconstruction, and Feature Space Hijacking Attacks
Split learning of deep neural networks (SplitNN) has provided a promising solution to learning jointly for the mutual interest of a guest and a host, which may come from different backgrounds, holding features partitioned vertically.
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