A new watermarking method for closed LLMs boosts random word-pair co-occurrences via rephrasing and detects the signal statistically in outputs, working reliably even when the watermarked data is only 1% of fine-tuning tokens while preserving utility.
Pratyush Maini, Hengrui Jia, Nicolas Papernot, and Adam Dziedzic
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Dataset Watermarking for Closed LLMs with Provable Detection
A new watermarking method for closed LLMs boosts random word-pair co-occurrences via rephrasing and detects the signal statistically in outputs, working reliably even when the watermarked data is only 1% of fine-tuning tokens while preserving utility.