Investigating Zero-shot Cross-lingual Language Understanding for Arabic DOI Creative Commons
Zaid Alyafeai, Moataz Ahmed

Published: Jan. 1, 2023

Numerous languages exhibit shared characteristics, especially in morphological features. For instance, Arabic and Russian both belong to the fusional language category. The question arises: Do such common traits influence comprehension across diverse linguistic backgrounds? This study explores possibility of transferring skills a zero-shot scenario. Specifically, we demonstrate that training models on other can enhance Arabic, as evidenced by our evaluations three key tasks: natural inference, answering, named entity recognition. Our experiments reveal certain morphologically rich (MRLs), Russian, display similarities when assessed context, particularly tasks like answering inference. However, this similarity is less pronounced

Language: Английский

Foundation and large language models: fundamentals, challenges, opportunities, and social impacts DOI

Devon Myers,

Rami Mohawesh,

Venkata Ishwarya Chellaboina

et al.

Cluster Computing, Journal Year: 2023, Volume and Issue: 27(1), P. 1 - 26

Published: Nov. 27, 2023

Language: Английский

Citations

58

NADI 2023: The Fourth Nuanced Arabic Dialect Identification Shared Task DOI Creative Commons
Muhammad Abdul-Mageed,

AbdelRahim Elmadany,

Chiyu Zhang

et al.

Published: Jan. 1, 2023

We describe the findings of fourth Nuanced Arabic Dialect Identification Shared Task (NADI 2023). The objective NADI is to help advance state-of-the-art NLP by creating opportunities for teams researchers collaboratively compete under standardized conditions. It does so with a focus on dialects, offering novel datasets and defining subtasks that allow meaningful comparisons between different approaches. 2023 targeted both dialect identification (Subtask1) dialect-to-MSA machine translation (Subtask 2 Subtask 3). A total 58 unique registered shared task, whom 18 have participated (with 76 valid submissions during test phase). Among these, 16 in 1, 5 2, 3 3. winning achieved 87.27 F1 14.76 Bleu 21.10 3, respectively. Results show all three remain challenging, thereby motivating future work this area. methods employed participating briefly offer an outlook NADI.

Language: Английский

Citations

17

Evaluating ChatGPT and Bard AI on Arabic Sentiment Analysis DOI Creative Commons
Abdulmohsen Al-Thubaity,

Sakhar Alkhereyf,

Hanan S. Murayshid

et al.

Published: Jan. 1, 2023

Abdulmohsen Al-Thubaity, Sakhar Alkhereyf, Hanan Murayshid, Nouf Alshalawi, Maha Omirah, Raghad Alateeq, Rawabi Almutairi, Razan Alsuwailem, Manal Alhassoun, Imaan Alkhanen. Proceedings of ArabicNLP 2023.

Language: Английский

Citations

10

Large Language Models for Arabic Sentiment Analysis and Machine Translation DOI Open Access
Mohamed Zouidine,

Mohammed Khalil

Engineering Technology & Applied Science Research, Journal Year: 2025, Volume and Issue: 15(2), P. 20737 - 20742

Published: April 3, 2025

Large Language Models (LLMs) have recently demonstrated outstanding performance in a variety of Natural Processing (NLP) tasks. Although many LLMs been developed, only few models evaluated the context Arabic language, with significant focus on ChatGPT model. This study assessed three two NLP tasks: sentiment analysis and machine translation. The capabilities LLaMA, Mixtral, Gemma under zero- few-shot learning were investigated, their was compared against State-Of-The-Art (SOTA) models. experimental results showed that, among models, LLaMA tends to better comprehension abilities for outperforming Mixtral both However, except Arabic-to-English translation, where outperforms transformer model by 4 BLEU points, all cases, fell behind that SOTA

Language: Английский

Citations

0

Evaluation of Ancient Chinese Natural Language Understanding in Large Language Models Based on ACHNLU DOI
Die Hu, Guangyao Sun, Liu Liu

et al.

Lecture notes in computer science, Journal Year: 2024, Volume and Issue: unknown, P. 3 - 18

Published: Jan. 1, 2024

Language: Английский

Citations

2

Investigating the Impact of Utilizing the ChatGPT for Arabic Sentiment Analysis DOI

Ghaleb Al-Gaphari,

Salah Al-Hagree,

Baligh Al-Helali

et al.

Lecture notes on data engineering and communications technologies, Journal Year: 2024, Volume and Issue: unknown, P. 93 - 107

Published: Jan. 1, 2024

Language: Английский

Citations

1

PTUK-HULAT at ArAIEval Shared Task Fine-tuned Distilbert to Predict Disinformative Tweets DOI Creative Commons
Areej Jaber, Paloma Martı́nez

Published: Jan. 1, 2023

Disinformation involves the dissemination of incomplete, inaccurate, or misleading information; it has objective, goal, purpose deliberately intentionally lying to others aboutthe truth. The spread disinformative information on social media serious implications, and causes concern among internet users in different aspects. Automatic classification models are required detect posts media, especially Twitter. In this article, DistilBERT multilingual model was fine-tuned classify tweets either as dis-informative not Subtask 2A ArAIEval shared task. system outperformed baseline achieved F1 micro 87% macro 80%. Our ranked 11 compared with all participants.

Language: Английский

Citations

1

Comparative Analysis of Copilot 4 and Chatgpt 4 for Literary Translation: A Comprehensive Evaluation DOI

RACHID ED-DALI

Published: Jan. 1, 2024

Download This Paper Open PDF in Browser Add to My Library Share: Permalink Using these links will ensure access this page indefinitely Copy URL DOI

Language: Английский

Citations

0

A Comprehensive Framework and Empirical Analysis for Evaluating Large Language Models in Arabic Dialect Identification DOI
Sadam Al-Azani, Nouf Alturayeif,

Haneen Abouelresh

et al.

2022 International Joint Conference on Neural Networks (IJCNN), Journal Year: 2024, Volume and Issue: 1, P. 1 - 7

Published: June 30, 2024

Language: Английский

Citations

0

Evaluating the Performance of LLMs When Translating Saudi Arabic as Low Resource Language DOI
Salwa Alahmari, Eric Atwell, Mohammad Ammar Alsalka

et al.

Lecture notes in computer science, Journal Year: 2024, Volume and Issue: unknown, P. 264 - 269

Published: Nov. 28, 2024

Language: Английский

Citations

0