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Budgeted token-event replacement evades KGW watermarks

Original title: Constructing Budgeted KGW Evasion through Token-Event Evidence Replacement

arXiv cs.CRby Hongliang Liu ()1 min read
AI summary · x-ai/grok-4.7Summaries by Vani AI

Phrase rewrites from an independent model remove watermark evidence at 16% token-edit cost in 39 of 82 tested passages.

KGW watermarks accumulate detection evidence through biased sampling. The authors construct budgeted evasion by jointly selecting phrase rewrites from an independent model and measuring global token-edit distance. Exact coverage search maximizes removal of original scored token pairs. Controlled tests on short passages show rewrites passing the detector at mean cost of 16.0% under a 20% allowance.

Key facts
  • 39 of 82 sources evaded with 16% token-edit cost
  • Mean suppression from removing watermark-enriched events
  • No advantage over simpler constrained rewriting
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From the original article

1 min read at arxiv.org

KGW watermarks bias sampling to accumulate keyed detection evidence. We construct budgeted evasion through token-event evidence replacement using ordinary phrase rewrites. Our construction jointly selects compositions of LLM-proposed alternatives from an independent model and measures global token-edit distance on complete outputs.

arXiv cs.CR

By Hongliang Liu · arxiv.org

Read the full article at arXiv cs.CR

A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.