Glow-AI/WaterDrum-Ax
WaterDrum: Watermarking for Data-centric Unlearning Metric WaterDrum provides an unlearning benchmark for the evaluation of the effectiveness and practicality of unlearning. The repository contains the ArXiv corpus of WaterDrum (WaterDrum-Ax), which contains both unwatermarked and watermarked ArXiv paper abstracts across 20 categories published after the release of the Llama-2 model. Each category contains 400 data samples, aggregating into 8000 samples in the full training set.… See the full description on the dataset page: https://huggingface.co/datasets/Glow-AI/WaterDrum-Ax.
| Author / organization | Glow-AI |
|---|---|
| License (as declared) | mit |
| Downloads | 568 (as reported by Hugging Face) |
| Likes | 9 |
| Created | 3 March 2025 |
| Last updated at source | 28 May 2026 |
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568 now (+22 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Recent changes
- 16 Oct 2026 Description: WaterDrum: Watermarking for Data-centric Unlearning Metric WaterDrum provides an unlearning benchmark for the evaluation of the effectiveness and practicality of unlearning. The repository contains the ArXiv corpus of WaterDrum (WaterDrum-A → WaterDrum: Watermarking for Data-centric Unlearning Metric WaterDrum provides an unlearning benchmark for the evaluation of the effectiveness and practicality of unlearning. The repository contains the ArXiv corpus of WaterDrum (WaterDrum-A
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