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    <abstract>This paper presents our participation in SemEval-2025 Task 11, which focuses on bridging the gap in text-based emotion detection. Our team took part in both Tracks A and B, addressing different aspects of emotion classification. We fine-tuned a RoBERTa base model on the provided dataset in Track A, achieving a Macro-F1 score of 0.7264. For Track B, we built on top of the Track A model by incorporating an additional non-linear layer, in the hope of enhancing Track A model’s understanding of emotion detection. Track B model resulted with an average Pearson’s R of 0.5658. The results demonstrate the effectiveness of fine-tuning in Track A and the potential improvements from architectural modifications in Track B for emotion intensity detection tasks.</abstract>
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%0 Conference Proceedings
%T CharsiuRice at SemEval-2025 Task 11: Bridging the Gap in Text-Based Emotion Detection
%A Yip, Hiu Yan
%A Chiu, Hing Man
%A Yang, Hai -. Yin
%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 yip-etal-2025-charsiurice
%X This paper presents our participation in SemEval-2025 Task 11, which focuses on bridging the gap in text-based emotion detection. Our team took part in both Tracks A and B, addressing different aspects of emotion classification. We fine-tuned a RoBERTa base model on the provided dataset in Track A, achieving a Macro-F1 score of 0.7264. For Track B, we built on top of the Track A model by incorporating an additional non-linear layer, in the hope of enhancing Track A model’s understanding of emotion detection. Track B model resulted with an average Pearson’s R of 0.5658. The results demonstrate the effectiveness of fine-tuning in Track A and the potential improvements from architectural modifications in Track B for emotion intensity detection tasks.
%U https://aclanthology.org/2025.semeval-1.143/
%P 1082-1088

Markdown (Informal)

[CharsiuRice at SemEval-2025 Task 11: Bridging the Gap in Text-Based Emotion Detection](https://aclanthology.org/2025.semeval-1.143/) (Yip et al., SemEval 2025)

• CharsiuRice at SemEval-2025 Task 11: Bridging the Gap in Text-Based Emotion Detection (Yip et al., SemEval 2025)

ACL

• Hiu Yan Yip, Hing Man Chiu, and Hai - Yin Yang. 2025. CharsiuRice at SemEval-2025 Task 11: Bridging the Gap in Text-Based Emotion Detection. In Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025), pages 1082–1088, Vienna, Austria. Association for Computational Linguistics.