jinzhuoran/RWKU
Dataset Card for Real-World Knowledge Unlearning Benchmark (RWKU) Dataset Summary RWKU is a real-world knowledge unlearning benchmark specifically designed for large language models (LLMs). This benchmark contains 200 real-world unlearning targets and 13,131 multi-level forget probes, including 3,268 fill-in-the-blank probes, 2,879 question-answer probes, and 6,984 adversarial-attack probes. RWKU is designed based on the following three key factors: For the task… See the full description on the dataset page: https://huggingface.co/datasets/jinzhuoran/RWKU.
| Author / organization | jinzhuoran |
|---|---|
| License (as declared) | cc-by-4.0 |
| Downloads | 6.9K (as reported by Hugging Face) |
| Likes | 9 |
| Created | 2 June 2024 |
| Last updated at source | 18 June 2024 |
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Recent changes
- 16 Oct 2026 Description: Dataset Card for Real-World Knowledge Unlearning Benchmark (RWKU) Dataset Summary RWKU is a real-world knowledge unlearning benchmark specifically designed for large language models (LLMs). This benchmark contains 200 real-world unlearning → Dataset Card for Real-World Knowledge Unlearning Benchmark (RWKU) Dataset Summary RWKU is a real-world knowledge unlearning benchmark specifically designed for large language models (LLMs). This benchmark contains 200 real-world unlearning
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