DEW is a semantic watermarking method for LLMs that derives a robust signal from dual embeddings via vector-space algebra and pseudo-random projections, remaining detectable after paraphrasing and translation.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , publisher =
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Robust Text Watermarking for Large Language Models via Dual Semantic Embeddings
DEW is a semantic watermarking method for LLMs that derives a robust signal from dual embeddings via vector-space algebra and pseudo-random projections, remaining detectable after paraphrasing and translation.