Jian-Yu Zhou

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2024

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NYCU-NLP at EXALT 2024: Assembling Large Language Models for Cross-Lingual Emotion and Trigger Detection
Tzu-Mi Lin | Zhe-Yu Xu | Jian-Yu Zhou | Lung-Hao Lee
Proceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis

This study describes the model design of the NYCU-NLP system for the EXALT shared task at the WASSA 2024 workshop. We instruction-tune several large language models and then assemble various model combinations as our main system architecture for cross-lingual emotion and trigger detection in tweets. Experimental results showed that our best performing submission is an assembly of the Starling (7B) and Llama 3 (8B) models. Our submission was ranked sixth of 17 participating systems for the emotion detection subtask, and fifth of 7 systems for the binary trigger detection subtask.
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