JGLUE: Japanese General Language Understanding Evaluation

Kentaro Kurihara, Daisuke Kawahara, Tomohide Shibata

研究成果: Conference contribution

11 被引用数 (Scopus)

抄録

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 (Wang et al., 2018), has been the forerunner, benchmarks are now being released for languages other than English, such as CLUE (Xu et al., 2020) for Chinese and FLUE (Le et al., 2020) 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.

本文言語English
ホスト出版物のタイトル2022 Language Resources and Evaluation Conference, LREC 2022
編集者Nicoletta Calzolari, Frederic Bechet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Helene Mazo, Jan Odijk, Stelios Piperidis
出版社European Language Resources Association (ELRA)
ページ2957-2966
ページ数10
ISBN(電子版)9791095546726
出版ステータスPublished - 2022
イベント13th International Conference on Language Resources and Evaluation Conference, LREC 2022 - Marseille, France
継続期間: 2022 6月 202022 6月 25

出版物シリーズ

名前2022 Language Resources and Evaluation Conference, LREC 2022

Conference

Conference13th International Conference on Language Resources and Evaluation Conference, LREC 2022
国/地域France
CityMarseille
Period22/6/2022/6/25

ASJC Scopus subject areas

  • 言語および言語学
  • 図書館情報学
  • 言語学および言語
  • 教育

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