Preprint Open access
Learning to Refer: Client-Resolved Generation for Privacy-Aware Language Models
Cloud-based large language models (LLMs) require users to disclose plaintext data to service providers, creating privacy risks in sensitive domains. Existing privacy-preserving approaches often trade utility for protection, incur substantial computational or communication overhead, remain vulnerable to reconstruction f …