Block-wise Codeword Embedding for Reliable Multi-bit Text Watermarking
Joeun Kim, HoEun Kim, Dongsup Jin, and Young-Sik Kim

TL;DR
This paper introduces BREW, a novel multi-bit watermarking framework for LLMs that significantly improves reliability by shifting from decoding to designated verification, reducing false positives.
Contribution
BREW presents a two-stage verification process that overcomes false positive issues in existing ECC-based watermarking methods, enabling reliable detection under local edits.
Findings
BREW achieves a TPR of 0.965 and an FPR of 0.02 under 10% synonym substitution.
Existing ECC-based extractors suffer from catastrophic false positives, which BREW effectively mitigates.
The framework is model-agnostic and theoretically grounded, scalable for forensic deployment.
Abstract
Recent multi-bit watermarking methods for large language models (LLMs) prioritize capacity over reliability, often conflating decoding with detection. Our analysis reveals that existing ECC-based extractors suffer from catastrophic false positive rates (FPR), and applying rejection thresholds merely collapses detection sensitivity (TPR) to random guessing. To resolve this structural limitation, we propose \textbf{BREW} (Block-wise Reliable Embedding for Watermarking), a framework shifting the paradigm to \emph{designated verification}. BREW employs a two-stage mechanism: (i) \textbf{blind message estimation} via independent block voting, followed by (ii) \textbf{window-shifting verification} that rigorously validates the payload against local edits. Experiments demonstrate that BREW achieves a TPR of 0.965 with an FPR of 0.02 under 10\% synonym substitution, demonstrating that the…
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