InferDPT: Privacy-Preserving Inference for Closed-box Large Language Model

Understand

Large language models (LLMs), like ChatGPT, have greatly simplified text generation tasks.

• However, they have also raised concerns about privacy risks such as data leakage and unauthorized data collection.
• Existing solutions for privacy-preserving inference face practical challenges related to computation time and communication costs.
• In this paper, we propose InferDPT, the first practical framework for the privacy-preserving Inference of black-box LLMs, implementing Differential Privacy in Text generation.