SOURCE-LINKED INTELLIGENCE
Semantic Watermarking with Order-Robust Detection over Sub-sentence Units
Semantic watermarks tie the mark to sentence meaning rather than token choices, promising robustness to content-preserving edits. However, the detector only observes attacker-supplied text, which can be reworded, reordered, or resegmented to evade detection without content loss. Rewording, reordering, and resegmentation all cause embedding displacement: detection tests embeddings different from those selected during watermarking and can therefore lose the mark. Our adaptive embedding displacement attack (EDA) admits all three edits under a single objective that maximizes this displacement. It
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-27T19:54:17.000Z
First collected: 2026-09-21T08:32:02.028Z. This is not the publication date.