Qin Liu

PI-SAFE: Practical Privacy-Preserving LLM Inference With Adversarial Fine-Tuning for Optimized Utility

Cloud-based Large Language Model (LLM) inference services typically require users to submit plain-text inputs, thereby posing severe privacy risks. Existing privacy-preserving paradigms are mostly task-specific and often necessitate pervasive modifications to the entire server-side model. This reliance introduces subst...