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arxiv 2502.16699 v2 pith:FA2RWIWG submitted 2025-02-23 cs.CL cs.LG

Evaluating the Robustness and Accuracy of Text Watermarking Under Real-World Cross-Lingual Manipulations

classification cs.CL cs.LG
keywords watermarkingcross-lingualmethodsscenariosadversarysettingscurrentdifferent
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We present a study to benchmark representative watermarking methods in cross-lingual settings. The current literature mainly focuses on the evaluation of watermarking methods for the English language. However, the literature for evaluating watermarking in cross-lingual settings is scarce. This results in overlooking important adversary scenarios in which a cross-lingual adversary could be in, leading to a gray area of practicality over cross-lingual watermarking. In this paper, we evaluate four watermarking methods in four different and vocabulary rich languages. Our experiments investigate the quality of text under different watermarking procedure and the detectability of watermarks with practical translation attack scenarios. Specifically, we investigate practical scenarios that an adversary with cross-lingual knowledge could take, and evaluate whether current watermarking methods are suitable for such scenarios. Finally, from our findings, we draw key insights about watermarking in cross-lingual settings.

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  1. SIF: Semantically In-Distribution Fingerprints for Large Vision-Language Models

    cs.CV 2026-04 unverdicted novelty 6.0

    SIF creates semantically in-distribution fingerprints for LVLMs by distilling text watermarks into visual inputs and optimizing for robustness against detection and modification.