Dataset · Hugging Face

AI-ISL/DUSK

Name: DUSK
Creator: AI-ISL
License: mit
Keywords: task_categories:question-answering, task_categories:multiple-choice, task_categories:other, annotations_creators:machine-generated, source_datasets:original, language:en, license:mit, size_categories:n<1K, format:parquet, modality:text, library:datasets, library:pandas, library:mlcroissant, library:polars, region:us

🌇 DUSK: Do Not Unlearn Shared Knowledge DUSK is a benchmark dataset designed for evaluating machine unlearning in multi-source settings, where specific data sources must be forgotten while preserving others. In realistic applications, documents often share factual overlap with publicly available content (e.g., Wikipedia, textbooks). DUSK challenges unlearning algorithms to precisely erase only what must be forgotten, while preserving knowledge that remains supported by other… See the full description on the dataset page: https://huggingface.co/datasets/AI-ISL/DUSK.

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Author / organization	AI-ISL
License (as declared)	mit
Downloads	255 (as reported by Hugging Face)
Likes	2
Created	26 April 2025
Last updated at source	16 May 2025

unlearningselective-forgettingmulti-sourcebenchmarklanguage-modelsDUSK

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