Probing Local Conditional Fit for Diffusion Model Membership Inference

Summary

Researchers propose LoFIT (Local Conditional Fit), a membership inference method for text-to-image diffusion models that measures the initial response of the denoising loss along normalized conditional prediction shifts. The method needs only forward queries to the denoiser, no target-model gradients. Across four datasets it improves membership discrimination on fine-tuned and pretrained models, and it separates members early in fine-tuning where the naive denoising-loss baseline stays near chance.

Topics

• Training data and privacy

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