UniMark: Unified Adaptive Multi-bit Watermarking for Autoregressive Image Generators
Invisible watermarking for autoregressive (AR) image generation has recently gained attention as a means of protecting image ownership and tracing AI-generated content. However, existing approaches suffer from three key limitations: (1) they embed only zero-bit watermarks for binary verification, lacking the ability to convey multi-bit messages; (2) they rely on static codebook partitioning strategies that are vulnerable to security attacks once the partition is exposed; and (3) they are designed for specific AR architectures, failing to generalize across diverse AR paradigms. We propose \method{}, a training-free, unified watermarking framework for autoregressive image generators that ad...
| Authors | Yigit Yilmaz, Elena Petrova, Mehmet Kaya et al. |
|---|---|
| Primary category | cs.CV |
| Published | 12 April 2026 |
| Last updated at source | 12 April 2026 |
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