From Construction to Injection: Edit-Based Fingerprints for Large Language Models
Researchers propose a novel fingerprinting framework for large language models that combines Code-mixing Fingerprints (CF) and Multi-Candidate Editing (MCEdit) to protect against unauthorized redistribution and commercial misuse. The approach addresses key vulnerabilities in existing fingerprinting methods by balancing imperceptibility with robustness against defensive filtering and downstream model modifications.