Position: The Term "Machine Unlearning" Is Overused in LLMs
arXiv:2606.27379v1 Announce Type: new Abstract: Large language models increasingly face demands to "forget" training data, knowledge, or behaviors due to regulatory deletion obligations, copyright/licensing disputes, and safety or product-policy requirements. This position paper argues that machine unlearning is overused as a term in LLM research and should be reserved for dataset-defined deletion: removing the training influence of a precisely specified forget set such that the resulting model ...
arXiv cs.CL
·Sangyeon Yoon, Yeachan Jun, Albert No
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