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Not to Break, but to Attest: Adversarial Probes for Privacy-Preserving LLM Verification
Post-deployment changes to large language models can alter behavior while leaving routine outputs largely unchanged, creating a challenge for AI governance when model weights are proprietary. We present a privacy-preserving zk-SNARK-based audit framework that searches for probes designed in the spir
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