Author

Xiang Li

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Preprint Aug 2026

Optimal Watermark Localization in Mixed-Source Large Language Model Texts

Watermarking provides a principled way to authenticate text generated by large language models (LLMs). In practice, however, the final text may be mixed-source, with watermark evidence surviving at only a subset of token positions after rewriting, insertion, deletion, or paraphrasing. Although prior work has studied gl...

José H. Blanchet, T. Cai, Xiang Li et al. · 0 citations

#machine learning Jun 2025

Optimal Estimation of Watermark Proportions in Hybrid AI-Human Texts

This paper addresses the problem of optimally estimating the watermark proportion in mixed-source texts, and proposes efficient estimators for this class of methods, and derive minimax lower bounds for any measurable estimator based on pivotal statistics, showing that their estimators achieve these lower bounds.

Xiang Li, Garrett Wen, Weiqing He et al. · arXiv.org · 5 citations · ⚡1