Targeted Counterfactual Fingerprinting for Black-Box LLM Ownership Verification
Large language models (LLMs) are high-value assets that can be derived through redeployment, fine-tuning, quantization, or further alignment. Because deployed LLMs are commonly exposed only through query APIs, ownership verification must often rely on black-box text responses. This setting is difficult: generations are open-ended and can vary across repeated queries, while existing black-box fingerprints rely on signals that are fragile under a final-response interface, including full-text matching, soft behavioral features, or model-specific prompts designed not to transfer. We propose TCF (Targeted Counterfactual Fingerprinting), a black-box LLM fingerprinting framework that converts op...
| Authors | Yutong Wu, Xiaofan Bai, Shixin Li et al. |
|---|---|
| Primary category | cs.CR |
| Published | 8 August 2026 |
| Last updated at source | 8 August 2026 |
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