@inproceedings{bashiti-etal-2025-imageeval,
title = "{I}mage{E}val 2025: The First {A}rabic Image Captioning Shared Task",
author = "Bashiti, Ahlam and
Aljabari, Alaa and
Hamoud, Hadi Khaled and
Biswas, Md. Rafiul and
Shalash, Bilal Mohammed and
Jarrar, Mustafa and
Zaraket, Fadi and
Mikros, George and
Asgari, Ehsaneddin and
Zaghouani, Wajdi",
editor = "Darwish, Kareem and
Ali, Ahmed and
Abu Farha, Ibrahim and
Touileb, Samia and
Zitouni, Imed and
Abdelali, Ahmed and
Al-Ghamdi, Sharefah and
Alkhereyf, Sakhar and
Zaghouani, Wajdi and
Khalifa, Salam and
AlKhamissi, Badr and
Almatham, Rawan and
Hamed, Injy and
Alyafeai, Zaid and
Alowisheq, Areeb and
Inoue, Go and
Mrini, Khalil and
Alshammari, Waad",
booktitle = "Proceedings of The Third Arabic Natural Language Processing Conference: Shared Tasks",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.arabicnlp-sharedtasks.52/",
pages = "376--389",
ISBN = "979-8-89176-356-2",
abstract = "We present ImageEval 2025, the first shared task dedicated to Arabic image captioning. The task addresses the critical gap in multimodal Arabic NLP by focusing on two complementary subtasks: (1) creating the first open-source, manually-captioned Arabic image dataset through a collaborative datathon, and (2) developing and evaluating Arabic image captioning models. A total of 44 teams registered, of which eight submitted during the test phase, producing 111 valid submissions. Evaluation was conducted using automatic metrics, LLM-based judgment, and human assessment. In Subtask 1, the best-performing system achieved a cosine similarity of 65.5, while in Subtask 2, the top score was 60.0. Although these results show encouraging progress, they also confirm that Arabic image captioning remains a challenging task, particularly due to cultural grounding requirements, morphological richness, and dialectal variation. All datasets, baseline models, and evaluation tools are released publicly to support future research in Arabic multimodal NLP."
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%0 Conference Proceedings
%T ImageEval 2025: The First Arabic Image Captioning Shared Task
%A Bashiti, Ahlam
%A Aljabari, Alaa
%A Hamoud, Hadi Khaled
%A Biswas, Md. Rafiul
%A Shalash, Bilal Mohammed
%A Jarrar, Mustafa
%A Zaraket, Fadi
%A Mikros, George
%A Asgari, Ehsaneddin
%A Zaghouani, Wajdi
%Y Darwish, Kareem
%Y Ali, Ahmed
%Y Abu Farha, Ibrahim
%Y Touileb, Samia
%Y Zitouni, Imed
%Y Abdelali, Ahmed
%Y Al-Ghamdi, Sharefah
%Y Alkhereyf, Sakhar
%Y Zaghouani, Wajdi
%Y Khalifa, Salam
%Y AlKhamissi, Badr
%Y Almatham, Rawan
%Y Hamed, Injy
%Y Alyafeai, Zaid
%Y Alowisheq, Areeb
%Y Inoue, Go
%Y Mrini, Khalil
%Y Alshammari, Waad
%S Proceedings of The Third Arabic Natural Language Processing Conference: Shared Tasks
%D 2025
%8 November
%I Association for Computational Linguistics
%C Suzhou, China
%@ 979-8-89176-356-2
%F bashiti-etal-2025-imageeval
%X We present ImageEval 2025, the first shared task dedicated to Arabic image captioning. The task addresses the critical gap in multimodal Arabic NLP by focusing on two complementary subtasks: (1) creating the first open-source, manually-captioned Arabic image dataset through a collaborative datathon, and (2) developing and evaluating Arabic image captioning models. A total of 44 teams registered, of which eight submitted during the test phase, producing 111 valid submissions. Evaluation was conducted using automatic metrics, LLM-based judgment, and human assessment. In Subtask 1, the best-performing system achieved a cosine similarity of 65.5, while in Subtask 2, the top score was 60.0. Although these results show encouraging progress, they also confirm that Arabic image captioning remains a challenging task, particularly due to cultural grounding requirements, morphological richness, and dialectal variation. All datasets, baseline models, and evaluation tools are released publicly to support future research in Arabic multimodal NLP.
%U https://aclanthology.org/2025.arabicnlp-sharedtasks.52/
%P 376-389
Markdown (Informal)
[ImageEval 2025: The First Arabic Image Captioning Shared Task](https://aclanthology.org/2025.arabicnlp-sharedtasks.52/) (Bashiti et al., ArabicNLP 2025)
ACL
- Ahlam Bashiti, Alaa Aljabari, Hadi Khaled Hamoud, Md. Rafiul Biswas, Bilal Mohammed Shalash, Mustafa Jarrar, Fadi Zaraket, George Mikros, Ehsaneddin Asgari, and Wajdi Zaghouani. 2025. ImageEval 2025: The First Arabic Image Captioning Shared Task. In Proceedings of The Third Arabic Natural Language Processing Conference: Shared Tasks, pages 376–389, Suzhou, China. Association for Computational Linguistics.