LUNAR’s “forgotten” knowledge can be resurrected, exposing unlearning limits
A red‑teaming analysis shows LUNAR’s unlearning can be bypassed: gradient‑based upstream edits and a simple activation shift retrieve the supposedly erased facts. The findings prove that current LLM unlearning methods merely hide knowledge, not delete it, raising safety concerns for any deployment that relies on true forgetting.