@inproceedings{zwawi-wu-2026-shu,
title = "{SHU} at {A}dab{E}val 2026: Category-Aware Fine-Tuning of {MARBERT} for {A}rabic Politeness and Pragmatic Function Classification",
author = "Zwawi, Alla and
Wu, Stephen",
editor = "Al-Khalifa, Hend and
El-Haj, Mo and
Ezzini, Saad",
booktitle = "The 7th Workshop on Open-Source {A}rabic Corpora and Processing Tools ({OSACT}7) with 5 Shared Tasks",
month = may,
year = "2026",
address = "Palma, Mallorca (Spain)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.osact-1.20/",
doi = "10.63317/5csq27bytjtc",
pages = "174--178",
abstract = "This paper describes our submission to the AdabEval 2026 shared task, addressing Subtask A (politeness classification) and Subtask B (multi-label pragmatic category prediction). For Subtask A, we fine-tuned MARBERT using weighted cross-entropy to mitigate class imbalance. For Subtask B, we apply BCEWithLogitsloss with inverse-frequency positive weighting to address the minority categories, and we introduce a category merging strategy to reduce categories' sparsity and annotation variation. Finally, we propose a stacked architecture where predicted pragmatic categories are injected as auxiliary features into the politeness classifier. Our results demonstrate that dialect-aware modelling, class-imbalance handling, and category-aware stacking improve Macro-F1 across both subtasks, achieving 0.85 for Subtask A and 0.55 for Subtask B on the test set."
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%0 Conference Proceedings
%T SHU at AdabEval 2026: Category-Aware Fine-Tuning of MARBERT for Arabic Politeness and Pragmatic Function Classification
%A Zwawi, Alla
%A Wu, Stephen
%Y Al-Khalifa, Hend
%Y El-Haj, Mo
%Y Ezzini, Saad
%S The 7th Workshop on Open-Source Arabic Corpora and Processing Tools (OSACT7) with 5 Shared Tasks
%D 2026
%8 May
%I Association for Computational Linguistics
%C Palma, Mallorca (Spain)
%F zwawi-wu-2026-shu
%X This paper describes our submission to the AdabEval 2026 shared task, addressing Subtask A (politeness classification) and Subtask B (multi-label pragmatic category prediction). For Subtask A, we fine-tuned MARBERT using weighted cross-entropy to mitigate class imbalance. For Subtask B, we apply BCEWithLogitsloss with inverse-frequency positive weighting to address the minority categories, and we introduce a category merging strategy to reduce categories’ sparsity and annotation variation. Finally, we propose a stacked architecture where predicted pragmatic categories are injected as auxiliary features into the politeness classifier. Our results demonstrate that dialect-aware modelling, class-imbalance handling, and category-aware stacking improve Macro-F1 across both subtasks, achieving 0.85 for Subtask A and 0.55 for Subtask B on the test set.
%R 10.63317/5csq27bytjtc
%U https://aclanthology.org/2026.osact-1.20/
%U https://doi.org/10.63317/5csq27bytjtc
%P 174-178
Markdown (Informal)
[SHU at AdabEval 2026: Category-Aware Fine-Tuning of MARBERT for Arabic Politeness and Pragmatic Function Classification](https://aclanthology.org/2026.osact-1.20/) (Zwawi & Wu, OSACT 2026)
ACL