Proposes causal fingerprints via causality-decoupling in pre-trained diffusion residual latent space for improved source attribution across GANs and diffusion models.
By fo- cusing on underlying causal relationships, we propose a formalized causal decoupling method and define causal fingerprints, filling a gap in model forensics research
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Causal Fingerprints of AI Generative Models
Proposes causal fingerprints via causality-decoupling in pre-trained diffusion residual latent space for improved source attribution across GANs and diffusion models.