arXiv (All)
open access
DRIFT: Removing Diffusion Watermarks by Deflecting the Generative Trajectory
Diffusion watermarking embeds verifiable signals into the generative process and commonly verifies them by recovering trajectory-dependent evidence, making the marks robust to conventional pixel-space distortions. Existing removal attacks either regenerate along deterministic trajectories, which oft
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- DRIFT: Removing Diffusion Watermarks by Deflecting the Generative Trajectory#667907
- AnchorMark: Robust Diffusion Watermarking via Latent-Space Rotation Synchrony#414053
- Removing the Watermark Is Not Enough: Forensic Stealth in Generative-AI Watermark Removal#684447
- Removing the Watermark Is Not Enough: Forensic Stealth in Generative-AI Watermark Removal#682672
- The Linear Geometry of Interpretable Tokens: Jailbreaking Attacks and Defenses for Unlearned Diffusion Models#635585
Record · ID 985586
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive