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llm-jp/AnswerCarefully

852 downloads in 30 days191 likesLast modified 20 Aug 2026View on Hugging Face
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The checks could not identify a recognised licence ID in the dataset's metadata.

Declared licence
other, from the tagEvidence: README.md at d1d4e57
Licence name on the card
answer-carefully-dataset-tou, link: LICENSEEvidence: README.md at d1d4e57
Licence files
LICENSE, LICENSE_ja, licence not identifiedEvidence: LICENSE at d1d4e57
Declared sources
None listed in the card metadata
Access gated on Hugging Face
Yes, manual approval required
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Citation text from the card

@inproceedings{suzuki-etal-2026-answercarefully,
  title = {AnswerCarefully: Creating a Dataset for LLM Safety in Japanese},
  author = {Suzuki, Hisami and Katsumata, Satoru and Kodama, Takashi and Takahashi, Tetsuro and Nakayama, Kouta and Sekine, Satoshi},
  booktitle = {Proceedings of the Fifteenth Language Resources and Evaluation Conference (LREC 2026)},
  month = {May},
  year = {2026},
  pages = {3921--3931},
  address = {Palma, Mallorca, Spain},
  publisher = {European Language Resources Association (ELRA)},
  editor = {Piperidis, Stelios and Bel, Núria and van den Heuvel, Henk and Ide, Nancy and Krek, Simon and Toral, Antonio},
  doi = {10.63317/289xxmwcworn},
  abstract = {In this paper we present JLLMSafety, a dataset for promoting the safety of Japanese LLM outputs. The dataset consists of 1,800 pairs of questions and reference answers, where the questions require special attention in answering. It covers a wide range of risk categories established in prior English-language datasets, but the data samples are original in that they are manually curated to reflect the socio-cultural context of LLM usage in Japan. We show that using this dataset for instruction to fine-tune a Japanese LLM led to improved output safety without compromising the utility of general responses. We also report the results of a safety evaluation of 12 Japanese LLMs using this dataset as a benchmark. Finally, we discuss the significance of creating regionally specific datasets of LLM safety, a

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dataset_licence({ "id": "llm-jp/AnswerCarefully" })
signal: "unclear"
stated_licence: "other"
sources: 0