AI RESEARCH
WIN-U: Woodbury-Informed Newton-Unlearning as a retain-free Machine Unlearning Framework
arXiv CS.LG
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ArXi:2604.13438v1 Announce Type: new Privacy concerns in LLMs have led to the rapidly growing need to enforce a data's "right to be forgotten". Machine unlearning addresses precisely this task, namely the removal of the influence of some specific data, i.e., the forget set, from a trained model. The gold standard for unlearning is to produce the model that would have been learned on only the rest of the