Collapse of Irrelevant Representations (CIR) Ensures Robust and Non-Disruptive LLM Unlearning

Current unlearning techniques and safety training consistently fail to remove dangerous knowledge from language models. We analyze the root causes and propose a highly selective technique which unlearns robustly and without disrupting general performance.