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nvidia/Nemotron-Content-Safety-Audio-Dataset

1,588 downloads in 30 days5 likesLast modified 1 Dec 2025View on Hugging Face
Permissive or share-alike

The declared licence (cc-by-4.0) is classified as permissive.

Declared licence
cc-by-4.0, from the tagEvidence: README.md at 8b90c94
Licence files
LICENSE, detected as cc-by-4.0Evidence: LICENSE at 8b90c94
Declared sources
1
Access gated on Hugging Face
No
nvidia/Nemotron-Content-Safety-Audio-Datasetnvidia/Nemotron-Con…cc-by-4.0: declared licencecc-by-4.0declared licenceREADME.md ↗cc-by-4.0: licence filecc-by-4.0licence fileLICENSE ↗nvidia/Aegis-AI-Content-Safety-Dataset-2.0: cc-by-4.0nvidia/Aegis-…cc-by-4.0README.md ↗
nvidia/Nemotron-Content-Safety-Audio-Datasetnvidia/Nemotron…cc-by-4.0: declared licencecc-by-4.0declared licenceREADME.md ↗cc-by-4.0: licence filecc-by-4.0licence fileLICENSE ↗nvidia/Aegis-AI-Content-Safety-Dataset-2.0: cc-by-4.0nvidia/Aegis-…cc-by-4.0README.md ↗
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Citation text from the card

@dataset{nemotron_audio_safety_2025,
  title = {Nemotron Content Safety Audio Dataset},
  author = {Hazare, Akshay},
  year = {2025},
  month = {December},
  publisher = {NVIDIA Corporation},
  url = {https://huggingface.co/datasets/nvidia/Nemotron-Content-Safety-Audio-Dataset},
  license = {CC-BY-4.0}
}

@inproceedings{ghosh-etal-2025-aegis2,
    title = "{AEGIS}2.0: A Diverse {AI} Safety Dataset and Risks Taxonomy for Alignment of {LLM} Guardrails",
    author = "Ghosh, Shaona and Varshney, Prasoon and Sreedhar, Makesh Narsimhan and Padmakumar, Aishwarya and Rebedea, Traian and Varghese, Jibin Rajan and Parisien, Christopher",
    editor = "Chiruzzo, Luis and Ritter, Alan and Wang, Lu",
    booktitle = "Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)",
    month = apr,
    year = "2025",
    address = "Albuquerque, New Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.naacl-long.306/",
    doi = "10.18653/v1/2025.naacl-long.306",
    pages = "5992--6026",
    ISBN = "979-8-89176-189-6"
}

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dataset_licence({ "id": "nvidia/Nemotron-Content-Safety-Audio-Dataset" })
signal: "permissive"
stated_licence: "cc-by-4.0"
sources: 1