De Zhang Lee
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126
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2026
Proof-of-Authorship for Diffusion-based AI Generated Content
The paper proposes a novel proof-of-authorship framework for AI-generated content by cryptographically binding the random seed used in latent diffusion model generation to the author's identity, offering a stronger guarantee than traditional ownership methods.
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