Cross-lingual and cross-country approaches to argument component detection: a comparative study.

Cecilia Graiff, Chloé Clavel, Benoît Sagot


Abstract
Argument mining in multilingual settings has rarely been investigated, due to the lack of annotated resources and to the inherent difficulty of the task. We benchmark the performance of models on cross-lingual and cross-country argument component detection, focusing on political data from the US and France. To do so, we introduce FrenchPolArg, a corpus of argumentative political discourse in French, and we automatically translate already existing US-English resources. We benchmark three different cross-lingual and cross-country pipelines, and compare their results to find the best-performing one. We obtain promising results to be integrated in semi-automatic annotation workflows to reduce the time and cost of annotations.
Anthology ID:
2026.mme-main.9
Volume:
Proceedings of the First Workshop on Multilingual Multicultural Evaluation
Month:
March
Year:
2026
Address:
Rabat, Morocco
Editors:
Pinzhen Chen, Vilém Zouhar, Hanxu Hu, Simran Khanuja, Wenhao Zhu, Barry Haddow, Alexandra Birch, Alham Fikri Aji, Rico Sennrich, Sara Hooker
Venues:
MME | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
149–161
Language:
URL:
https://aclanthology.org/2026.mme-main.9/
DOI:
Bibkey:
Cite (ACL):
Cecilia Graiff, Chloé Clavel, and Benoît Sagot. 2026. Cross-lingual and cross-country approaches to argument component detection: a comparative study.. In Proceedings of the First Workshop on Multilingual Multicultural Evaluation, pages 149–161, Rabat, Morocco. Association for Computational Linguistics.
Cite (Informal):
Cross-lingual and cross-country approaches to argument component detection: a comparative study. (Graiff et al., MME 2026)
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PDF:
https://aclanthology.org/2026.mme-main.9.pdf