@inproceedings{a9b836593afd431e8500b92513bbc92e,
title = "GARI: Graph Attention for Relative Isomorphism of Arabic Word Embeddings",
abstract = "Bilingual Lexical Induction (BLI) is a core challenge in NLP, it relies on the relative isomorphism of individual embedding spaces. Existing attempts aimed at controlling the relative isomorphism of different embedding spaces fail to incorporate the impact of semantically related words in the model training objective. To address this, we propose GARI that combines the distributional training objectives with multiple isomorphism losses guided by the graph attention network. GARI considers the impact of semantical variations of words in order to define the relative isomorphism of the embedding spaces. Experimental evaluation using the Arabic language data set shows that GARI outperforms the existing research by improving the average P@1 by a relative score of up to 40.95% and 76.80% for in-domain and domain mismatch settings respectively. We release the codes for GARI at https://github.com/asif6827/GARI.",
author = "Ali, {Muhammad Asif} and Maha Alshmrani and Jianbin Qin and Yan Hu and Di Wang",
note = "Publisher Copyright: {\textcopyright} 2023 Association for Computational Linguistics.; 1st Arabic Natural Language Processing Conference, ArabicNLP 2023 ; Conference date: 07-12-2023",
year = "2023",
language = "English (US)",
series = "ArabicNLP 2023 - 1st Arabic Natural Language Processing Conference, Proceedings",
publisher = "Association for Computational Linguistics (ACL)",
pages = "181--190",
editor = "Hassan Sawaf and Samhaa El-Beltagy and Wajdi Zaghouani and Walid Magdy and Nadi Tomeh and {Abu Farha}, Ibrahim and Nizar Habash and Salam Khalifa and Amr Keleg and Hatem Haddad and Imed Zitouni and Ahmed Abdelali and Khalil Mrini and Rawan Almatham",
booktitle = "ArabicNLP 2023 - 1st Arabic Natural Language Processing Conference, Porceedings",
address = "United States",
}