WaterSeeker introduces a novel approach to efficiently identify watermarked LLM-generated text segments within larger human-authored documents.

• Addresses a real-world challenge current watermarking methods overlook
• Balances computational efficiency with detection accuracy
• Creates a practical solution for identifying AI-generated content in mixed-source documents
• Strengthens content authentication in security-sensitive contexts

This research is crucial for security professionals working to verify content authenticity, detect potential misuse of AI systems, and maintain trust in digital environments where human and AI-generated content increasingly coexist.

WaterSeeker: Pioneering Efficient Detection of Watermarked Segments in Large Documents