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Data Provenance Auditing of Fine-Tuned Large Language Models with a Text-Preserving Technique
We propose a system for marking sensitive or copyrighted texts to detect their use in fine-tuning large language models under black-box access with statistical guarantees. Our method builds digital ``marks'' using invisible Unicode characters organized into (``cue'', ``reply'') pairs. During an audi
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