@inproceedings{takahashi-etal-2026-ozemi,
title = "{OZ}emi at {S}em{E}val-2026 Task 9: A Cross-Lingual Approach to Online Text Polarization Classification Using Multilingual Models and Adaptive Loss Formulation",
author = "Takahashi, Hidetsune and
Nusi Tee, Eleale and
Yu, Aika and
Furukawa, Ruri and
Kim, Sooeun and
Niinomi, Shuta and
Zhang, Dingyu and
Ohman, Emily",
editor = "Kochmar, Ekaterina and
Ghosh, Debanjan and
North, Kai and
Komachi, Mamoru",
booktitle = "Proceedings of the 20th {I}nternational {W}orkshop on {S}emantic {E}valuation (2026)",
month = jul,
year = "2026",
address = "San Diego, California, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.semeval-1.27/",
pages = "182--192",
ISBN = "979-8-89176-414-9",
abstract = "This paper presents the OZemi team{'}s submission to SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization.We propose a unified multilingual approach that addresses multiple languages and subtasks efficiently. Our system combines multilingual models with data-level techniques and a class-weighted cross-entropy loss to mitigate data imbalance across languages, subtasks, and categories. Results show consistent performance across languages, achieving macro F1 scores above 70{\%} in most languages for Subtask 1 achieving our highest rank in subtask 1 for Persian (1 out of 44). These results suggest that the proposed framework provides a flexible foundation for multilingual and multi-task polarization analysis."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="takahashi-etal-2026-ozemi">
<titleInfo>
<title>OZemi at SemEval-2026 Task 9: A Cross-Lingual Approach to Online Text Polarization Classification Using Multilingual Models and Adaptive Loss Formulation</title>
</titleInfo>
<name type="personal">
<namePart type="given">Hidetsune</namePart>
<namePart type="family">Takahashi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Eleale</namePart>
<namePart type="family">Nusi Tee</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Aika</namePart>
<namePart type="family">Yu</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ruri</namePart>
<namePart type="family">Furukawa</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Sooeun</namePart>
<namePart type="family">Kim</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Shuta</namePart>
<namePart type="family">Niinomi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Dingyu</namePart>
<namePart type="family">Zhang</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Emily</namePart>
<namePart type="family">Ohman</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2026-07</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 20th International Workshop on Semantic Evaluation (2026)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Ekaterina</namePart>
<namePart type="family">Kochmar</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Debanjan</namePart>
<namePart type="family">Ghosh</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Kai</namePart>
<namePart type="family">North</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Mamoru</namePart>
<namePart type="family">Komachi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">San Diego, California, USA</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
<identifier type="isbn">979-8-89176-414-9</identifier>
</relatedItem>
<abstract>This paper presents the OZemi team’s submission to SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization.We propose a unified multilingual approach that addresses multiple languages and subtasks efficiently. Our system combines multilingual models with data-level techniques and a class-weighted cross-entropy loss to mitigate data imbalance across languages, subtasks, and categories. Results show consistent performance across languages, achieving macro F1 scores above 70% in most languages for Subtask 1 achieving our highest rank in subtask 1 for Persian (1 out of 44). These results suggest that the proposed framework provides a flexible foundation for multilingual and multi-task polarization analysis.</abstract>
<identifier type="citekey">takahashi-etal-2026-ozemi</identifier>
<location>
<url>https://aclanthology.org/2026.semeval-1.27/</url>
</location>
<part>
<date>2026-07</date>
<extent unit="page">
<start>182</start>
<end>192</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T OZemi at SemEval-2026 Task 9: A Cross-Lingual Approach to Online Text Polarization Classification Using Multilingual Models and Adaptive Loss Formulation
%A Takahashi, Hidetsune
%A Nusi Tee, Eleale
%A Yu, Aika
%A Furukawa, Ruri
%A Kim, Sooeun
%A Niinomi, Shuta
%A Zhang, Dingyu
%A Ohman, Emily
%Y Kochmar, Ekaterina
%Y Ghosh, Debanjan
%Y North, Kai
%Y Komachi, Mamoru
%S Proceedings of the 20th International Workshop on Semantic Evaluation (2026)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, USA
%@ 979-8-89176-414-9
%F takahashi-etal-2026-ozemi
%X This paper presents the OZemi team’s submission to SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization.We propose a unified multilingual approach that addresses multiple languages and subtasks efficiently. Our system combines multilingual models with data-level techniques and a class-weighted cross-entropy loss to mitigate data imbalance across languages, subtasks, and categories. Results show consistent performance across languages, achieving macro F1 scores above 70% in most languages for Subtask 1 achieving our highest rank in subtask 1 for Persian (1 out of 44). These results suggest that the proposed framework provides a flexible foundation for multilingual and multi-task polarization analysis.
%U https://aclanthology.org/2026.semeval-1.27/
%P 182-192
Markdown (Informal)
[OZemi at SemEval-2026 Task 9: A Cross-Lingual Approach to Online Text Polarization Classification Using Multilingual Models and Adaptive Loss Formulation](https://aclanthology.org/2026.semeval-1.27/) (Takahashi et al., SemEval 2026)
ACL
- Hidetsune Takahashi, Eleale Nusi Tee, Aika Yu, Ruri Furukawa, Sooeun Kim, Shuta Niinomi, Dingyu Zhang, and Emily Ohman. 2026. OZemi at SemEval-2026 Task 9: A Cross-Lingual Approach to Online Text Polarization Classification Using Multilingual Models and Adaptive Loss Formulation. In Proceedings of the 20th International Workshop on Semantic Evaluation (2026), pages 182–192, San Diego, California, USA. Association for Computational Linguistics.