ELYADATA at NADI 2024 shared task: Arabic Dialect Identification with Similarity-Induced Mono-to-Multi Label Transformation.
Amira Karoui, Farah Gharbi, Rami Kammoun, Imen Laouirine, Fethi Bougares
Correct Metadata for
Abstract
This paper describes our submissions to the Multi-label Country-level Dialect Identification subtask of the NADI2024 shared task, organized during the second edition of the ArabicNLP conference. Our submission is based on the ensemble of fine-tuned BERT-based models, after implementing the Similarity-Induced Mono-to-Multi Label Transformation (SIMMT) on the input data. Our submission ranked first with a Macro-Average (MA) F1 score of 50.57%.- Anthology ID:
- 2024.arabicnlp-1.85
- Volume:
- Proceedings of the Second Arabic Natural Language Processing Conference
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand
- Editors:
- Nizar Habash, Houda Bouamor, Ramy Eskander, Nadi Tomeh, Ibrahim Abu Farha, Ahmed Abdelali, Samia Touileb, Injy Hamed, Yaser Onaizan, Bashar Alhafni, Wissam Antoun, Salam Khalifa, Hatem Haddad, Imed Zitouni, Badr AlKhamissi, Rawan Almatham, Khalil Mrini
- Venues:
- ArabicNLP | WS
- SIG:
- SIGARAB
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 758–763
- Language:
- URL:
- https://aclanthology.org/2024.arabicnlp-1.85/
- DOI:
- 10.18653/v1/2024.arabicnlp-1.85
- Bibkey:
- Cite (ACL):
- Amira Karoui, Farah Gharbi, Rami Kammoun, Imen Laouirine, and Fethi Bougares. 2024. ELYADATA at NADI 2024 shared task: Arabic Dialect Identification with Similarity-Induced Mono-to-Multi Label Transformation.. In Proceedings of the Second Arabic Natural Language Processing Conference, pages 758–763, Bangkok, Thailand. Association for Computational Linguistics.
- Cite (Informal):
- ELYADATA at NADI 2024 shared task: Arabic Dialect Identification with Similarity-Induced Mono-to-Multi Label Transformation. (Karoui et al., ArabicNLP 2024)
- Copy Citation:
- PDF:
- https://aclanthology.org/2024.arabicnlp-1.85.pdf
Export citation
@inproceedings{karoui-etal-2024-elyadata,
title = "{ELYADATA} at {NADI} 2024 shared task: {A}rabic Dialect Identification with Similarity-Induced Mono-to-Multi Label Transformation.",
author = "Karoui, Amira and
Gharbi, Farah and
Kammoun, Rami and
Laouirine, Imen and
Bougares, Fethi",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh, Nadi and
Abu Farha, Ibrahim and
Abdelali, Ahmed and
Touileb, Samia and
Hamed, Injy and
Onaizan, Yaser and
Alhafni, Bashar and
Antoun, Wissam and
Khalifa, Salam and
Haddad, Hatem and
Zitouni, Imed and
AlKhamissi, Badr and
Almatham, Rawan and
Mrini, Khalil",
booktitle = "Proceedings of the Second Arabic Natural Language Processing Conference",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.arabicnlp-1.85/",
doi = "10.18653/v1/2024.arabicnlp-1.85",
pages = "758--763",
abstract = "This paper describes our submissions to the Multi-label Country-level Dialect Identification subtask of the NADI2024 shared task, organized during the second edition of the ArabicNLP conference. Our submission is based on the ensemble of fine-tuned BERT-based models, after implementing the Similarity-Induced Mono-to-Multi Label Transformation (SIMMT) on the input data. Our submission ranked first with a Macro-Average (MA) F1 score of 50.57{\%}."
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%0 Conference Proceedings %T ELYADATA at NADI 2024 shared task: Arabic Dialect Identification with Similarity-Induced Mono-to-Multi Label Transformation. %A Karoui, Amira %A Gharbi, Farah %A Kammoun, Rami %A Laouirine, Imen %A Bougares, Fethi %Y Habash, Nizar %Y Bouamor, Houda %Y Eskander, Ramy %Y Tomeh, Nadi %Y Abu Farha, Ibrahim %Y Abdelali, Ahmed %Y Touileb, Samia %Y Hamed, Injy %Y Onaizan, Yaser %Y Alhafni, Bashar %Y Antoun, Wissam %Y Khalifa, Salam %Y Haddad, Hatem %Y Zitouni, Imed %Y AlKhamissi, Badr %Y Almatham, Rawan %Y Mrini, Khalil %S Proceedings of the Second Arabic Natural Language Processing Conference %D 2024 %8 August %I Association for Computational Linguistics %C Bangkok, Thailand %F karoui-etal-2024-elyadata %X This paper describes our submissions to the Multi-label Country-level Dialect Identification subtask of the NADI2024 shared task, organized during the second edition of the ArabicNLP conference. Our submission is based on the ensemble of fine-tuned BERT-based models, after implementing the Similarity-Induced Mono-to-Multi Label Transformation (SIMMT) on the input data. Our submission ranked first with a Macro-Average (MA) F1 score of 50.57%. %R 10.18653/v1/2024.arabicnlp-1.85 %U https://aclanthology.org/2024.arabicnlp-1.85/ %U https://doi.org/10.18653/v1/2024.arabicnlp-1.85 %P 758-763
Markdown (Informal)
[ELYADATA at NADI 2024 shared task: Arabic Dialect Identification with Similarity-Induced Mono-to-Multi Label Transformation.](https://aclanthology.org/2024.arabicnlp-1.85/) (Karoui et al., ArabicNLP 2024)
- ELYADATA at NADI 2024 shared task: Arabic Dialect Identification with Similarity-Induced Mono-to-Multi Label Transformation. (Karoui et al., ArabicNLP 2024)
ACL
- Amira Karoui, Farah Gharbi, Rami Kammoun, Imen Laouirine, and Fethi Bougares. 2024. ELYADATA at NADI 2024 shared task: Arabic Dialect Identification with Similarity-Induced Mono-to-Multi Label Transformation.. In Proceedings of the Second Arabic Natural Language Processing Conference, pages 758–763, Bangkok, Thailand. Association for Computational Linguistics.