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Ze-Wen Sun

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#artificial intelligence Preprint Sep 2026

Beyond Semantic Narrowing: Robust and Efficient LLM Watermarking with Hamming Neighborhoods

Semantic watermarking improves robustness against watermark removal attacks by embedding detectable signals into sentence-level representations. However, existing watermarking methods typically impose watermark-specific semantic preferences on generated sentences without explicitly accounting for the highly non-uniform...

Ze-Wen Sun, Tong-Yang Zhao, Li-Yao Xiang et al. · 0 citations

Jul 2026

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency

This work proposes an LLM watermarking scheme \textit{WaterMoE} for the growingly popular Mixture-of-Experts (MoE) LLMs that achieves a fidelity performance close to the unwatermarked and consistently outperforms state-of-the-art watermarking methods on the benchmark.

Ze-Wen Sun, Qian Jiang, Si-Yuan Sheng et al. · arXiv.org · 0 citations