@inproceedings{zhu-etal-2026-quantilemark,
title = "{Q}uantile{M}ark: A Message-Symmetric Multi-bit Watermark for {LLM}s",
author = "Zhu, Junlin and
Huang, Baizhou and
Wan, Xiaojun",
editor = "Liakata, Maria and
Moreira, Viviane P. and
Zhang, Jiajun and
Jurgens, David",
booktitle = "Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
month = jul,
year = "2026",
address = "San Diego, California, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.acl-long.308/",
pages = "6790--6806",
ISBN = "979-8-89176-390-6",
abstract = "As large language models become standard backends for content generation, practical provenance increasingly requires multi-bit watermarking. In provider-internal deployments, a key requirement is message symmetry: the message itself should not systematically affect either text quality or verification outcomes.Vocabulary-partition watermarks can break message symmetry in low-entropy decoding: some messages are assigned most of the probability mass, while others are forced to use tail tokens. This makes embedding quality and message decoding accuracy message-dependent.We propose QuantileMark, a white-box multi-bit watermark that embeds messages within the continuous cumulative probability interval $[0, 1)$.At each step, QuantileMark partitions this interval into $M$ equal-mass bins and samples strictly from the bin assigned to the target symbol, ensuring a fixed $1/M$ probability budget regardless of context entropy.For detection, the verifier reconstructs the same partition under teacher forcing, computes posteriors over latent bins, and aggregates evidence for verification.We prove message-unbiasedness, a property ensuring that the base distribution is recovered when averaging over messages. This provides a theoretical foundation for generation-side symmetry, while the equal-mass design additionally promotes uniform evidence strength across messages on the detection side.Empirical results on C4 continuation and LFQA show improved multi-bit recovery and detection robustness over strong baselines, with negligible impact on generation quality."
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<abstract>As large language models become standard backends for content generation, practical provenance increasingly requires multi-bit watermarking. In provider-internal deployments, a key requirement is message symmetry: the message itself should not systematically affect either text quality or verification outcomes.Vocabulary-partition watermarks can break message symmetry in low-entropy decoding: some messages are assigned most of the probability mass, while others are forced to use tail tokens. This makes embedding quality and message decoding accuracy message-dependent.We propose QuantileMark, a white-box multi-bit watermark that embeds messages within the continuous cumulative probability interval [0, 1).At each step, QuantileMark partitions this interval into M equal-mass bins and samples strictly from the bin assigned to the target symbol, ensuring a fixed 1/M probability budget regardless of context entropy.For detection, the verifier reconstructs the same partition under teacher forcing, computes posteriors over latent bins, and aggregates evidence for verification.We prove message-unbiasedness, a property ensuring that the base distribution is recovered when averaging over messages. This provides a theoretical foundation for generation-side symmetry, while the equal-mass design additionally promotes uniform evidence strength across messages on the detection side.Empirical results on C4 continuation and LFQA show improved multi-bit recovery and detection robustness over strong baselines, with negligible impact on generation quality.</abstract>
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%0 Conference Proceedings
%T QuantileMark: A Message-Symmetric Multi-bit Watermark for LLMs
%A Zhu, Junlin
%A Huang, Baizhou
%A Wan, Xiaojun
%Y Liakata, Maria
%Y Moreira, Viviane P.
%Y Zhang, Jiajun
%Y Jurgens, David
%S Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, United States
%@ 979-8-89176-390-6
%F zhu-etal-2026-quantilemark
%X As large language models become standard backends for content generation, practical provenance increasingly requires multi-bit watermarking. In provider-internal deployments, a key requirement is message symmetry: the message itself should not systematically affect either text quality or verification outcomes.Vocabulary-partition watermarks can break message symmetry in low-entropy decoding: some messages are assigned most of the probability mass, while others are forced to use tail tokens. This makes embedding quality and message decoding accuracy message-dependent.We propose QuantileMark, a white-box multi-bit watermark that embeds messages within the continuous cumulative probability interval [0, 1).At each step, QuantileMark partitions this interval into M equal-mass bins and samples strictly from the bin assigned to the target symbol, ensuring a fixed 1/M probability budget regardless of context entropy.For detection, the verifier reconstructs the same partition under teacher forcing, computes posteriors over latent bins, and aggregates evidence for verification.We prove message-unbiasedness, a property ensuring that the base distribution is recovered when averaging over messages. This provides a theoretical foundation for generation-side symmetry, while the equal-mass design additionally promotes uniform evidence strength across messages on the detection side.Empirical results on C4 continuation and LFQA show improved multi-bit recovery and detection robustness over strong baselines, with negligible impact on generation quality.
%U https://aclanthology.org/2026.acl-long.308/
%P 6790-6806
Markdown (Informal)
[QuantileMark: A Message-Symmetric Multi-bit Watermark for LLMs](https://aclanthology.org/2026.acl-long.308/) (Zhu et al., ACL 2026)
ACL
- Junlin Zhu, Baizhou Huang, and Xiaojun Wan. 2026. QuantileMark: A Message-Symmetric Multi-bit Watermark for LLMs. In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 6790–6806, San Diego, California, United States. Association for Computational Linguistics.