MUSE is a comprehensive machine unlearning evaluation benchmark that assesses six key properties for unlearned models: (1) no verbatim memorization, (2) no knowledge memorization, (3) no privacy leakage, (4) utility preservation on data not intended for removal, (5) scalability with respect to the size of removal requests, and (6) sustainability over sequential unlearning requests. MUSE focuses on two types of textual data that commonly require unlearning: news articles… See the full description on the dataset page:
https://huggingface.co/datasets/muse-bench/MUSE-News.
