@inproceedings{shlkamy-zaghouani-2026-northwestern-12,
title = "Northwestern 12 at Daleel 2026: {CAM}e{LBERT}-Mix for Multi-Label {A}rabic Argumentative Discourse Unit Classification",
author = "Shlkamy, Eman Sedqy and
Zaghouani, Wajdi",
editor = "Abdul-Mageed, Muhammad and
Elsayed, Tamer and
Bouamor, Houda and
El-Beltagy, Samhaa and
Al-Khalifa, Hend and
Abdelali, Ahmed and
Elmadany, AbdelRahim and
El Mekki, Abdellah and
Darwish, Kareem and
Alkhereyf, Sakhar and
Luqman, Hamzah and
Khalifa, Salam and
Magdy, Samar and
Alyafeai, Zaid and
Hamed, Injy and
Zaghouani, Wajdi and
Zitouni, Imed",
booktitle = "Proceedings of The Fourth {A}rabic Natural Language Processing Conference: Shared Tasks",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.arabicnlp-sharedtasks.167/",
pages = "1344--1348",
ISBN = "979-8-89176-497-2",
abstract = "This paper presents our submission to Task{~}1 (Argumentative Discourse Unit Classification, Closed Track) of the Daleel 2026 Shared Task. The task addresses Arabic multi-label argumentative discourse unit classification at the paragraph level. Our system fine-tunes CAMeLBERT-Mix using a class-weighted Binary Cross-Entropy loss, paragraph-type-aware input representation, head-tail tokenization for long paragraphs, and label-specific threshold optimization. On the official development set, the proposed system achieves a Macro F1-score of 0.6121, a Micro F1-score of 0.7509, and a Samples F1-score of 0.6387. These results suggest that a carefully optimized CAMeLBERT-Mix framework provides a competitive and reproducible approach for Arabic argumentative discourse unit classification under the Closed Track setting."
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<abstract>This paper presents our submission to Task 1 (Argumentative Discourse Unit Classification, Closed Track) of the Daleel 2026 Shared Task. The task addresses Arabic multi-label argumentative discourse unit classification at the paragraph level. Our system fine-tunes CAMeLBERT-Mix using a class-weighted Binary Cross-Entropy loss, paragraph-type-aware input representation, head-tail tokenization for long paragraphs, and label-specific threshold optimization. On the official development set, the proposed system achieves a Macro F1-score of 0.6121, a Micro F1-score of 0.7509, and a Samples F1-score of 0.6387. These results suggest that a carefully optimized CAMeLBERT-Mix framework provides a competitive and reproducible approach for Arabic argumentative discourse unit classification under the Closed Track setting.</abstract>
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%0 Conference Proceedings
%T Northwestern 12 at Daleel 2026: CAMeLBERT-Mix for Multi-Label Arabic Argumentative Discourse Unit Classification
%A Shlkamy, Eman Sedqy
%A Zaghouani, Wajdi
%Y Abdul-Mageed, Muhammad
%Y Elsayed, Tamer
%Y Bouamor, Houda
%Y El-Beltagy, Samhaa
%Y Al-Khalifa, Hend
%Y Abdelali, Ahmed
%Y Elmadany, AbdelRahim
%Y El Mekki, Abdellah
%Y Darwish, Kareem
%Y Alkhereyf, Sakhar
%Y Luqman, Hamzah
%Y Khalifa, Salam
%Y Magdy, Samar
%Y Alyafeai, Zaid
%Y Hamed, Injy
%Y Zaghouani, Wajdi
%Y Zitouni, Imed
%S Proceedings of The Fourth Arabic Natural Language Processing Conference: Shared Tasks
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-497-2
%F shlkamy-zaghouani-2026-northwestern-12
%X This paper presents our submission to Task 1 (Argumentative Discourse Unit Classification, Closed Track) of the Daleel 2026 Shared Task. The task addresses Arabic multi-label argumentative discourse unit classification at the paragraph level. Our system fine-tunes CAMeLBERT-Mix using a class-weighted Binary Cross-Entropy loss, paragraph-type-aware input representation, head-tail tokenization for long paragraphs, and label-specific threshold optimization. On the official development set, the proposed system achieves a Macro F1-score of 0.6121, a Micro F1-score of 0.7509, and a Samples F1-score of 0.6387. These results suggest that a carefully optimized CAMeLBERT-Mix framework provides a competitive and reproducible approach for Arabic argumentative discourse unit classification under the Closed Track setting.
%U https://aclanthology.org/2026.arabicnlp-sharedtasks.167/
%P 1344-1348
Markdown (Informal)
[Northwestern 12 at Daleel 2026: CAMeLBERT-Mix for Multi-Label Arabic Argumentative Discourse Unit Classification](https://aclanthology.org/2026.arabicnlp-sharedtasks.167/) (Shlkamy & Zaghouani, ArabicNLP 2026)
ACL