論文 ·日本語 ·未確認

JGLUE: Japanese General Language Understanding Evaluation

Kentaro Kurihara Daisuke Kawahara Tomohide Shibata

刊行年
2022-01-01
収録
『Journal of Natural Language Processing』 29(2) pp. 2957-2966
言語
英語
openalex
W4285178177
doi
10.5715/jnlp.29.711
issn
1340-7619
URL
https://www.jstage.jst.go.jp/article/jnlp/29/2/29_711/_pdf

要旨

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.

主題

この書誌の出所

  • openalex— W4285178177(2026-08-13取得)

引用キー: Kurihara2022JGLUE

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