@inproceedings{al-qasem-2026-rabeeqasem,
title = "{R}abee{Q}asem - {I}mpact{A}i at Daleel 2026: Conformer-Based {A}rabic Argumentative Discourse Mining",
author = "Al-Qasem, Rabee",
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.165/",
pages = "1323--1327",
ISBN = "979-8-89176-497-2",
abstract = "We present our system for Daleel 2026 Task 2 on Arabic Argumentative Discourse Unit (ADU) detection. Our main contribution is a Conformer-based tagging architecture that combines a pretrained AraBERT encoder with a Conformer head to capture both global discourse context and local span-boundary cues. To the best of our knowledge, this is the first application of a Conformer-based architecture to Arabic ADU detection. The system also uses overlapping token windows, class-weighted training, character-level span reconstruction, and lightweight post-processing. On the official hidden test set, our system achieved an overall F1 score of 0.732, substantially outperforming the official baseline of 0.285 and ranking fourth in the closed track."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="al-qasem-2026-rabeeqasem">
<titleInfo>
<title>RabeeQasem - ImpactAi at Daleel 2026: Conformer-Based Arabic Argumentative Discourse Mining</title>
</titleInfo>
<name type="personal">
<namePart type="given">Rabee</namePart>
<namePart type="family">Al-Qasem</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2026-10</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of The Fourth Arabic Natural Language Processing Conference: Shared Tasks</title>
</titleInfo>
<name type="personal">
<namePart type="given">Muhammad</namePart>
<namePart type="family">Abdul-Mageed</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Tamer</namePart>
<namePart type="family">Elsayed</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Houda</namePart>
<namePart type="family">Bouamor</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Samhaa</namePart>
<namePart type="family">El-Beltagy</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Hend</namePart>
<namePart type="family">Al-Khalifa</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ahmed</namePart>
<namePart type="family">Abdelali</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">AbdelRahim</namePart>
<namePart type="family">Elmadany</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Abdellah</namePart>
<namePart type="family">El Mekki</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Kareem</namePart>
<namePart type="family">Darwish</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Sakhar</namePart>
<namePart type="family">Alkhereyf</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Hamzah</namePart>
<namePart type="family">Luqman</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Salam</namePart>
<namePart type="family">Khalifa</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Samar</namePart>
<namePart type="family">Magdy</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Zaid</namePart>
<namePart type="family">Alyafeai</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Injy</namePart>
<namePart type="family">Hamed</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Wajdi</namePart>
<namePart type="family">Zaghouani</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Imed</namePart>
<namePart type="family">Zitouni</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Budapest, Hungary</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
<identifier type="isbn">979-8-89176-497-2</identifier>
</relatedItem>
<abstract>We present our system for Daleel 2026 Task 2 on Arabic Argumentative Discourse Unit (ADU) detection. Our main contribution is a Conformer-based tagging architecture that combines a pretrained AraBERT encoder with a Conformer head to capture both global discourse context and local span-boundary cues. To the best of our knowledge, this is the first application of a Conformer-based architecture to Arabic ADU detection. The system also uses overlapping token windows, class-weighted training, character-level span reconstruction, and lightweight post-processing. On the official hidden test set, our system achieved an overall F1 score of 0.732, substantially outperforming the official baseline of 0.285 and ranking fourth in the closed track.</abstract>
<identifier type="citekey">al-qasem-2026-rabeeqasem</identifier>
<location>
<url>https://aclanthology.org/2026.arabicnlp-sharedtasks.165/</url>
</location>
<part>
<date>2026-10</date>
<extent unit="page">
<start>1323</start>
<end>1327</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T RabeeQasem - ImpactAi at Daleel 2026: Conformer-Based Arabic Argumentative Discourse Mining
%A Al-Qasem, Rabee
%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 al-qasem-2026-rabeeqasem
%X We present our system for Daleel 2026 Task 2 on Arabic Argumentative Discourse Unit (ADU) detection. Our main contribution is a Conformer-based tagging architecture that combines a pretrained AraBERT encoder with a Conformer head to capture both global discourse context and local span-boundary cues. To the best of our knowledge, this is the first application of a Conformer-based architecture to Arabic ADU detection. The system also uses overlapping token windows, class-weighted training, character-level span reconstruction, and lightweight post-processing. On the official hidden test set, our system achieved an overall F1 score of 0.732, substantially outperforming the official baseline of 0.285 and ranking fourth in the closed track.
%U https://aclanthology.org/2026.arabicnlp-sharedtasks.165/
%P 1323-1327
Markdown (Informal)
[RabeeQasem - ImpactAi at Daleel 2026: Conformer-Based Arabic Argumentative Discourse Mining](https://aclanthology.org/2026.arabicnlp-sharedtasks.165/) (Al-Qasem, ArabicNLP 2026)
ACL