Preprint Open access
Preemptive LLM Unlearning against Forbidden Capability Acquisition via Gradient Sealing
Open-weight LLMs are released not only as fixed products but also as substrates for downstream fine-tuning. This openness, however, creates legal and ethical risks because users may misuse fine-tuning to instill illicit knowledge or enable hostile operations. Model providers therefore need apre-release defense against …