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On the Information-Theoretic Limits of Latent-Space Watermarking Through Pretrained Generators
We study latent-space watermarking through a pretrained generator using a prescribed latent-to-output stochastic mapping, called the renderer. A watermark encoder selects the latent input using a message and secret key. For every message and semantic context, the released output must have exactly th
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