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cs.CV2026
On the Robustness of Watermarking for Autoregressive Image Generation
Andreas Müller, Denis Lukovnikov, Shingo Kodama +5
The proliferation of autoregressive (AR) image generators demands reliable detection and attribution of their outputs to mitigate misinformation, and to filter synthetic images fro…
cs.CV2026
ClusterMark: Towards Robust Watermarking for Autoregressive Image Generators with Visual Token Clustering
Denis Lukovnikov, Andreas Müller, Erwin Quiring +1
In-generation watermarking for latent diffusion models has recently shown high robustness in marking generated images for easier detection and attribution. However, its application…