KBF uses stable numerical recall near the knowledge boundary to fingerprint and audit black-box LLM APIs, successfully detecting all tested substitutions and some real-world inconsistencies across production endpoints.
Rofl: Robust fingerprinting of language models.arXiv preprint arXiv:2505.12682
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SeedPrints fingerprints LLMs using persistent biases from initialization seeds for lineage verification across pretraining and adaptation stages.
LLM DNA is introduced as a low-dimensional bi-Lipschitz functional representation proven to satisfy inheritance and genetic determinism, with a training-free extraction pipeline tested on 305 models to reveal relationships and construct phylogenetic trees.
A survey of LLM copyright protection that unifies text watermarking, model watermarking, and model fingerprinting while presenting new coverage of fingerprint transfer and removal.
citing papers explorer
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KBF: Knowledge Boundary as Fingerprint for Language Model and Black-Box API Auditing
KBF uses stable numerical recall near the knowledge boundary to fingerprint and audit black-box LLM APIs, successfully detecting all tested substitutions and some real-world inconsistencies across production endpoints.
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SeedPrints: Fingerprints Can Even Tell Which Seed Your Large Language Model Was Trained From
SeedPrints fingerprints LLMs using persistent biases from initialization seeds for lineage verification across pretraining and adaptation stages.
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LLM DNA: Tracing Model Evolution via Functional Representations
LLM DNA is introduced as a low-dimensional bi-Lipschitz functional representation proven to satisfy inheritance and genetic determinism, with a training-free extraction pipeline tested on 305 models to reveal relationships and construct phylogenetic trees.
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Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trends
A survey of LLM copyright protection that unifies text watermarking, model watermarking, and model fingerprinting while presenting new coverage of fingerprint transfer and removal.