zhouyijiang1 at SemEval-2025 Task 11: A Multi-tag Detection Method based on Pre-training Language Models

Zhou Jiang, Dengtao Zhang


Abstract
In order to effectively predict the speaker’s informing emotion from text fragments, we propose a transfer learning framework based on the BERT pre-training model through deep semantic feature extraction and cascade structure of dynamic weight linear classifier. In the speaker informing emotion prediction task, a 0.70 F1 score is achieved, illustrating the effectiveness of cross-domain emotion recognition.
Anthology ID:
2025.semeval-1.147
Volume:
Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)
Month:
July
Year:
2025
Address:
Vienna, Austria
Editors:
Sara Rosenthal, Aiala Rosá, Debanjan Ghosh, Marcos Zampieri
Venues:
SemEval | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1113–1117
Language:
URL:
https://preview.aclanthology.org/corrections-2025-08/2025.semeval-1.147/
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Bibkey:
Cite (ACL):
Zhou Jiang and Dengtao Zhang. 2025. zhouyijiang1 at SemEval-2025 Task 11: A Multi-tag Detection Method based on Pre-training Language Models. In Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025), pages 1113–1117, Vienna, Austria. Association for Computational Linguistics.
Cite (Informal):
zhouyijiang1 at SemEval-2025 Task 11: A Multi-tag Detection Method based on Pre-training Language Models (Jiang & Zhang, SemEval 2025)
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https://preview.aclanthology.org/corrections-2025-08/2025.semeval-1.147.pdf