From TDMA to CDMA: A Multi-bit Watermark for Diffusion Language Models
Baizhou Huang, Xiaojun Wan
Abstract
While DLMs have emerged as an alternative to ARMs, robust content provenance mechanisms for this architecture remain unexplored. Existing multi-bit watermarking schemes, heavily reliant on the sequential generation of ARMs, cannot be directly applied to DLMs. In this paper, we reframe the multi-bit watermarking problem through a novel Digital Signal Processing (DSP) lens. We draw an analogy between prior works and TDMA (Time Division Multiple Access), revealing their inherent limitations. To overcome these limitations, we introduce CDMArk, the first multi-bit watermarking framework tailored for DLMs, orchestrating a paradigm shift from TDMA to CDMA (Code Division Multiple Access). CDMArk encodes the entire watermark message across all token positions holographically. We further provide rigorous statistical guarantees for its detection process. Extensive experiments demonstrate that CDMArk achieves a new state-ofthe-art Pareto frontier between imperceptibility and effectiveness.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 4a1846e6-d212-405f-ab74-683c5e88f3dfBuilds on15
- Structured Denoising Diffusion Models in Discrete State-SpacesJacob Austin, Daniel D. Johnson, Jonathan Ho, Daniel Tarlow et al.NeurIPS 2021 · 2,256 citations
- Large Language Diffusion ModelsShen Nie, Fengqi Zhu, Zebin You, Xiaolu Zhang et al.NeurIPS 2025 · 949 citations
- Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defenseKalpesh Krishna, Yixiao Song, Marzena Karpinska, John Wieting et al.NeurIPS 2023 · 657 citations
- Discrete Diffusion Modeling by Estimating the Ratios of the Data DistributionAaron Lou, Chenlin Meng, Stefano ErmonICML 2024 · 473 citations
- LLaDA 1.5: Variance-Reduced Preference Optimization for Large Language Diffusion ModelsFengqi Zhu, Rongzhen Wang, Shen Nie, Xiaolu Zhang et al.ACL 2026 · 229 citations
Related papers
- Watermarking Diffusion Language ModelsThibaud Gloaguen, Robin Staab, Nikola Jovanović, Martin VechevICLR 2026 · 13 citations
- dgMARK: Decoding-Guided Watermarking for Diffusion Language ModelsPyo Min Hong, Albert NoICML 2026
- You Can Have a Second Chance: Unbiased and Multi-bit Watermarking for Diffusion Language Models with Regret-based RemaskingKe Yang, Dongyang Liang, Jing Yu, Shuguang Yuan et al.ACL 2026
- XMark: Reliable Multi-Bit Watermarking for LLM-Generated TextsJiahao Xu, Rui Hu, Olivera Kotevska, Zikai ZhangACL 2026 · 1 citation
- IPMark: A Sentence-Level Watermark for LLMs with Hierarchical Personalization and Efficient DetectionWenbo An, Lianwei Wu, Zehao WangICML 2026
