Model Fingerprinting
Model fingerprinting is a sophisticated technique used to identify and track large language models through their unique characteristics. This approach enables model owners to protect their intellectual property and verify model authenticity in various deployment scenarios.
🔍 Non-invasive Methods
Explore methods that leverage inherent model properties without requiring architectural modifications. These techniques extract fingerprints from weight space, feature space, or through prompt optimization strategies.
Learn More →⚡ Invasive Methods
Discover approaches that involve model modifications during training or architectural design. These methods embed specific information through digital watermarks or fingerprint patterns for targeted extraction.
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