AI RESEARCH
Prompt2Fingerprint: Plug-and-Play LLM Fingerprinting via Text-to-Weight Generation
arXiv CS.LG
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ArXi:2605.18474v1 Announce Type: cross 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.