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Paper · arXiv

Prompt2Fingerprint: Plug-and-Play LLM Fingerprinting via Text-to-Weight Generation

The widespread deployment and redistribution of large language models (LLMs) have made model provenance tracking a critical challenge. While existing LLM fingerprinting methods, particularly active approaches that embed identity signals via fine-tuning, achieve high accuracy and robustness, they suffer from significant scalability bottlenecks. These methods typically treat fingerprint injection as an independent, one-off optimization task rather than a reusable capability, necessitating separate, resource-intensive training for every new identity. This incurs prohibitive computational costs and deployment delays. To address this, we propose Prompt2Fingerprint (P2F), the first framework th...

AuthorsSixu Chen, Xiang Chen, Hongyao Yu et al.
Primary categorycs.CR
Published18 May 2026
Last updated at source19 May 2026
cs.CRcs.AIcs.CLcs.LG
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