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        <title>Team KiAmSo at SemEval-2025 Task 11: A Comparison of Classification Models for Multi-label Emotion Detection</title>
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    <abstract>The aim of this paper is to take on the challenge of multi-label emotion detection for a variety of languages as part of Track A in SemEval 2025 Task 11: Bridging the Gap in Text-Based Emotion Detection. We fine-tune different pre-trained mono- and multilingual language models and compare their performance on multi-label emotion detection on a variety of high-resource and low-resource languages. Overall, we find that monolingual models tend to perform better, but for low-resource languages that do not have state-of-the-art pre-trained language models, multilingual models can achieve comparable results.</abstract>
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%0 Conference Proceedings
%T Team KiAmSo at SemEval-2025 Task 11: A Comparison of Classification Models for Multi-label Emotion Detection
%A Sharp, Kimberly
%A Kathmann, Sofia
%A Rüeck, Amelie
%Y Rosenthal, Sara
%Y Rosá, Aiala
%Y Ghosh, Debanjan
%Y Zampieri, Marcos
%S Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-273-2
%F sharp-etal-2025-team
%X The aim of this paper is to take on the challenge of multi-label emotion detection for a variety of languages as part of Track A in SemEval 2025 Task 11: Bridging the Gap in Text-Based Emotion Detection. We fine-tune different pre-trained mono- and multilingual language models and compare their performance on multi-label emotion detection on a variety of high-resource and low-resource languages. Overall, we find that monolingual models tend to perform better, but for low-resource languages that do not have state-of-the-art pre-trained language models, multilingual models can achieve comparable results.
%U https://aclanthology.org/2025.semeval-1.203/
%P 1542-1548

Markdown (Informal)

[Team KiAmSo at SemEval-2025 Task 11: A Comparison of Classification Models for Multi-label Emotion Detection](https://aclanthology.org/2025.semeval-1.203/) (Sharp et al., SemEval 2025)

• Team KiAmSo at SemEval-2025 Task 11: A Comparison of Classification Models for Multi-label Emotion Detection (Sharp et al., SemEval 2025)

ACL

• Kimberly Sharp, Sofia Kathmann, and Amelie Rüeck. 2025. Team KiAmSo at SemEval-2025 Task 11: A Comparison of Classification Models for Multi-label Emotion Detection. In Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025), pages 1542–1548, Vienna, Austria. Association for Computational Linguistics.