A Comprehensive Framework and Empirical Analysis for Evaluating Large Language Models in Arabic Dialect Identification-Reference-Cited by-同舟云学术

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A Comprehensive Framework and Empirical Analysis for Evaluating Large Language Models in Arabic Dialect Identification

Published:2024-06-30 Issue: Volume:1 Page:1-7
ISSN:
Container-title:2024 International Joint Conference on Neural Networks (IJCNN)
language:
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Author:

Al-Azani Sadam¹,Alturayeif Nora²,Abouelresh Haneen¹,Alhunief Alhanoof¹

Affiliation:

1. King Fahd University of Petroleum & Minerals,SDAIA-KFUPM Joint Research Center for Artificial Intelligence,Dhahran,Saudi Arabia

2. Imam Abdulrahman Bin Faisal University,Department of Computer Science,Dammam,Saudi Arabia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10649807/10649898/10651099.pdf?arnumber=10651099

Reference27 articles.

1. Improving language understanding by generative pre-training;Radford;OpenAI,2018

2. Language models are unsupervised multitask learners;Radford;OpenAI blog,2019

3. Language models are few-shot learners;Brown;Advances in neural information processing systems,2020

4. Bert: Pre-training of deep bidirectional transformers for language understanding;Devlin,2018

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