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Arxiv
1d
105
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SoK: Watermarking for AI-Generated Content
- Watermarking schemes are being considered as a way to differentiate between AI-generated content and human-created content.
- These schemes involve embedding hidden signals within AI-generated content for reliable detection.
- Although not a complete solution, watermarking can contribute significantly to AI safety and trustworthiness by combating misinformation and deception.
- The paper provides an extensive overview of watermarking techniques for generative AI, starting with the necessity of watermarking from historical and regulatory standpoints.
- The definitions and desired properties of watermarking schemes are formalized in the paper, along with an analysis of key objectives and threat models.
- The study also delves into practical evaluation strategies to develop robust watermarking techniques that can withstand various attacks.
- Recent works in this area are reviewed, open challenges are outlined, and potential future directions for watermarking in generative AI are discussed.
- The aim of the paper is to guide researchers in improving watermarking methods and applications and aid policymakers in addressing the broader implications of generative AI.
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