ChainMark: Model-Free LLM Watermarking with Closed-Form Calibration
Regulatory regimes such as the EU AI Act mandate machine-readable marking of synthetic text, but existing watermark detectors rely on the generating LM and on heuristic thresholds with no closed-form calibration. We introduce ChainMark, an active watermark that partitions the vocabulary into S states via keyed SHA-256 and forces a hard Markov transition on a fraction rho of positions; the detector replays the partition from the same key in O(n) hash operations, with no LM access. We derive a closed-form S*(n, rho, alpha) mapping a target FPR, text length, and budget to the minimum state count (Theorem 1), prove a universal robustness threshold delta* = 1 - 1/sqrt(2) approximately 29.3% th...
| Authors | Chengheng Li-Chen, Kyuhee Kim |
|---|---|
| Primary category | cs.CR |
| Published | 20 July 2026 |
| Last updated at source | 20 July 2026 |
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