src_fb50be84b835134c75
- Source-provided label
- Not reported
- Evidence class
- mentioned in report
- Confidence
- Not reported
- Observed
- Oct 07, 2026 04:00 UTC
- Retrieved
- Oct 08, 2026 03:43 UTC
Rethinking Visual Provenance: Detection and Watermarking Across Direct Visual Generation and LLM-Driven Code Rendering
arXiv:2610.08137v1 Announce Type: new Abstract: AI systems create images and videos with image/video generation models or by writing code and graphics descriptions that are then rendered. These routes can produce similar visible artifacts but expose different representations, intervention points, and provenance evidence. We develop a production-centered framework that compares detection and waterm
Reference details
- Source category
- Research & news
- Report title
Rethinking Visual Provenance: Detection and Watermarking Across Direct Visual Generation and LLM-Driven Code Rendering- First reported
- Oct 07, 2026 04:00 UTC
- Last reported
- Oct 07, 2026 04:00 UTC
- Catalog updated
- Oct 08, 2026 03:43 UTC
- Record ID
c0591145fb3cf3b1a78ca4844d6edeba72a6186e8a5db8d2effb36cc1d88ca14
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1 sources: 0 stale, 0 needing attention, 0 paused, 1 unverified.
Review source update dates and status
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