Papers with fingerprinting methods

3 papers
Ghost in the Shell: Synonym-Aware Logit Shaping Fingerprint for Copyright Protection of Large Vision-Language Models (2026.findings-acl)

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Challenge: Existing fingerprinting methods for large vision-language models rely on backdoors to elicit abnormal outputs, but direct distortion of the model’s original outputs compromises modality alignment and degrades multimodal capabilities.
Approach: They propose to embed a robust fingerprint while preserving the original normal outputs of the model.
Outcome: The proposed fingerprint maintains multimodal performance and substantially enhances fingerprint robustness.
EverTracer: Hunting Stolen Large Language Models via Stealthy and Robust Probabilistic Fingerprint (2025.emnlp-main)

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Challenge: Existing fingerprinting methods require impractical white-box access or introduce detectable statistical anomalies.
Approach: They propose a gray-box fingerprinting framework that ensures stealthy and robust model provenance tracing.
Outcome: The proposed framework is the first to repurpose Membership Inference Attacks (MIAs) for defensive use, embedding ownership signals via memorization instead of artificial trigger-output overfitting.
MEraser: An Effective Fingerprint Erasure Approach for Large Language Models (2025.acl-long)

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Challenge: Large Language Models (LLMs) have raised critical concerns about model ownership and intellectual property protection.
Approach: They propose a method for effectively removing backdoor-based fingerprints from LLMs . they propose deleting backdoor fingerprints using a transferable erasure mechanism .
Outcome: The proposed method removes backdoor-based fingerprints while maintaining model performance.

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