CSF: Black-box Fingerprinting via Compositional Semantics for Text-to-Image Models
Text-to-image models are commercially valuable assets often distributed under restrictive licenses, but such licenses are enforceable only when violations can be detected. Existing methods require pre-deployment watermarking or internal model access, which are unavailable in commercial API deployments. We present Compositional Semantic Fingerprinting (CSF), the first black-box method for attributing fine-tuned text-to-image models to protected lineages using only query access. CSF treats models as semantic category generators and probes them with compositional underspecified prompts that remain rare under fine-tuning. This gives IP owners an asymmetric advantage: new prompt compositions c...
| Authors | Junhoo Lee, Mijin Koo, Nojun Kwak |
|---|---|
| Primary category | cs.CR |
| Published | 20 March 2026 |
| Last updated at source | 20 March 2026 |
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