AINeutralarXiv – CS AI · Apr 106/10
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Towards Privacy-Preserving Large Language Model: Text-free Inference Through Alignment and Adaptation
Researchers introduce Privacy-Preserving Fine-Tuning (PPFT), a novel training approach that enables LLM services to process user queries without receiving raw text, addressing privacy vulnerabilities in current deployments. The method uses client-side encoders and noise-injected embeddings to maintain competitive model performance while eliminating exposure of sensitive personal, medical, or legal information.