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Paper · arXiv

Selective Disclosure Watermarking for Large Language Models

Watermarking methods embed imperceptible and verifiable signals into text generated by large language models (LLMs). Existing approaches include zero-bit schemes for distinguishing synthetic text from human writing and multi-bit schemes for embedding metadata. However, current multi-bit watermarking methods do not allow selective disclosure: verifying any part of the watermark requires revealing the entire embedded message. This lack of control leads to unnecessary information exposure and raises privacy concerns. We propose Hierarchical Vocabulary Routing (HeRo), a watermarking framework that enables selective disclosure of embedded metadata. The method recursively partitions the vocabul...

AuthorsXuyang Chen, Xiang Li, Yangxinyu Xie et al.
Primary categorycs.CR
Published6 July 2026
Last updated at source6 July 2026
cs.CRcs.AIcs.CLcs.LG
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