数据集:
llm-book/JGLUE
JGLUE是用于评估日语自然语言理解能力的基准测试集。详情请参考 the original repository 。
本作品采用知识共享署名-相同方式共享4.0国际许可协议。
@inproceedings{kurihara-etal-2022-jglue, title = "{JGLUE}: {J}apanese General Language Understanding Evaluation", author = "Kurihara, Kentaro and Kawahara, Daisuke and Shibata, Tomohide", booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference", month = jun, year = "2022", address = "Marseille, France", publisher = "European Language Resources Association", url = "https://aclanthology.org/2022.lrec-1.317", pages = "2957--2966", abstract = "To develop high-performance natural language understanding (NLU) models, it is necessary to have a benchmark to evaluate and analyze NLU ability from various perspectives. While the English NLU benchmark, GLUE, has been the forerunner, benchmarks are now being released for languages other than English, such as CLUE for Chinese and FLUE for French; but there is no such benchmark for Japanese. We build a Japanese NLU benchmark, JGLUE, from scratch without translation to measure the general NLU ability in Japanese. We hope that JGLUE will facilitate NLU research in Japanese.", }
@InProceedings{Kurihara_nlp2022, author = "栗原健太郎 and 河原大輔 and 柴田知秀", title = "JGLUE: 日本語言語理解ベンチマーク", booktitle = "言語処理学会第 28 回年次大会", year = "2022", url = "https://www.anlp.jp/proceedings/annual_meeting/2022/pdf_dir/E8-4.pdf" note= "in Japanese" }
感谢 Kentaro Kurihara 、 Daisuke Kawahara 和 Tomohide Shibata 创建了该数据集。
与Hugging Face datasets集成的代码最初由 Shunsuke Kitada 编写,经过 this repository 的改编。