Interpreting Arabic Transformer Models: A Study on XAI Interpretability for Quranic Semantic Search Models

Transformers have shown their effectiveness in various machine learning tasks. However, their "black box" nature often obscures their decision-making processes, particularly in Arabic, posing a barrier to their broader adoption and trust. This study delves into the interpretability...

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書誌詳細

出版年:	Jordanian Journal of Computers and Information Technology
主要な著者:	Ahmad M. Mustafa, Saja Nakhleh, Rama Irsheidat, Raneem Alruosan
フォーマット:	論文
言語:	英語
出版事項:	Scientific Research Support Fund of Jordan (SRSF) and Princess Sumaya University for Technology (PSUT) 2024-04-01
主題:	arabic nlp explainable machine learning semantic search transformers
オンライン･アクセス:	https://www.jjcit.org/?mno=184722