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A Watermark Detector Learns Its Own Family Tree
Training against frozen legacy embedders preserves old marks while angular diversity separates new embedder generations.
Summary
Training against frozen legacy embedders preserves old marks while angular diversity separates new embedder generations.
The method addresses an embedder-collapse effect that can raise false positives against versions a detector was not meant to recognize. The authors report near-perfect true-negative recovery without measurable loss in detection accuracy or audio quality on their tests; that is not a universal robustness guarantee.
Why it matters
Training against frozen legacy embedders preserves old marks while angular diversity separates new embedder generations.
Limits and context
- The method addresses an embedder-collapse effect that can raise false positives against versions a detector was not meant to recognize.
- The authors report near-perfect true-negative recovery without measurable loss in detection accuracy or audio quality on their tests; that is not a universal robustness guarantee.
Key claims
Training against frozen legacy embedders preserves old marks while angular diversity separates new embedder generations.
Qualification: The method addresses an embedder-collapse effect that can raise false positives against versions a detector was not meant to recognize.
Evidence: source-2026-10-16-020
Sources
- arXiv preprint 2610.22296, original v1arXiv / submitting research authors · primary research
Corrections
No corrections have been recorded for this story.