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

doi:10.18653/v1/2024.wassa-1.50

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

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Abstract

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.

Anthology ID:: 2024.wassa-1.50
Volume:: Proceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis
Month:: August
Year:: 2024
Address:: Bangkok, Thailand
Editors:: Orphée De Clercq, Valentin Barriere, Jeremy Barnes, Roman Klinger, João Sedoc, Shabnam Tafreshi
Venues:: WASSA | WS
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 505–510
Language:
URL:: https://aclanthology.org/2024.wassa-1.50/
DOI:: 10.18653/v1/2024.wassa-1.50
Bibkey:
Cite (ACL):: Tzu-Mi Lin, Zhe-Yu Xu, Jian-Yu Zhou, and Lung-Hao Lee. 2024. NYCU-NLP at EXALT 2024: Assembling Large Language Models for Cross-Lingual Emotion and Trigger Detection. In Proceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis, pages 505–510, Bangkok, Thailand. Association for Computational Linguistics.
Cite (Informal):: NYCU-NLP at EXALT 2024: Assembling Large Language Models for Cross-Lingual Emotion and Trigger Detection (Lin et al., WASSA 2024)
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PDF:: https://aclanthology.org/2024.wassa-1.50.pdf

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@inproceedings{lin-etal-2024-nycu,
    title = "{NYCU}-{NLP} at {EXALT} 2024: Assembling Large Language Models for Cross-Lingual Emotion and Trigger Detection",
    author = "Lin, Tzu-Mi  and
      Xu, Zhe-Yu  and
      Zhou, Jian-Yu  and
      Lee, Lung-Hao",
    editor = "De Clercq, Orph{\'e}e  and
      Barriere, Valentin  and
      Barnes, Jeremy  and
      Klinger, Roman  and
      Sedoc, Jo{\~a}o  and
      Tafreshi, Shabnam",
    booktitle = "Proceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, {\&} Social Media Analysis",
    month = aug,
    year = "2024",
    address = "Bangkok, Thailand",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.wassa-1.50/",
    doi = "10.18653/v1/2024.wassa-1.50",
    pages = "505--510",
    abstract = "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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%0 Conference Proceedings
%T NYCU-NLP at EXALT 2024: Assembling Large Language Models for Cross-Lingual Emotion and Trigger Detection
%A Lin, Tzu-Mi
%A Xu, Zhe-Yu
%A Zhou, Jian-Yu
%A Lee, Lung-Hao
%Y De Clercq, Orphée
%Y Barriere, Valentin
%Y Barnes, Jeremy
%Y Klinger, Roman
%Y Sedoc, João
%Y Tafreshi, Shabnam
%S Proceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F lin-etal-2024-nycu
%X 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.
%R 10.18653/v1/2024.wassa-1.50
%U https://aclanthology.org/2024.wassa-1.50/
%U https://doi.org/10.18653/v1/2024.wassa-1.50
%P 505-510

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Markdown (Informal)

[NYCU-NLP at EXALT 2024: Assembling Large Language Models for Cross-Lingual Emotion and Trigger Detection](https://aclanthology.org/2024.wassa-1.50/) (Lin et al., WASSA 2024)

NYCU-NLP at EXALT 2024: Assembling Large Language Models for Cross-Lingual Emotion and Trigger Detection (Lin et al., WASSA 2024)

ACL

Tzu-Mi Lin, Zhe-Yu Xu, Jian-Yu Zhou, and Lung-Hao Lee. 2024. NYCU-NLP at EXALT 2024: Assembling Large Language Models for Cross-Lingual Emotion and Trigger Detection. In Proceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis, pages 505–510, Bangkok, Thailand. Association for Computational Linguistics.