Bootstrap The Original Latent: Learning a Private Model from a Black-box Model

Understand

In this paper, considering the balance of data/model privacy of model owners and user needs, we propose a new setting called Back-Propagated Black-Box Adaptation (BPBA) for users to better train their private models via the guidance of the back-propagated results of a Black-box foundation/source model.

• Our setting can ease the usage of foundation/source models as well as prevent the leakage and misuse of foundation/source models.
• Moreover, we also propose a new training strategy called Bootstrap The Original Latent (BTOL) to fully utilize the foundation/source models.
• Our strategy consists of a domain adapter and a freeze-and-thaw strategy.