Papers with CHEER-Ekman

1 papers
CHEER-Ekman: Fine-grained Embodied Emotion Classification (2025.acl-short)

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Challenge: Emotions manifest through physical experiences and bodily reactions, yet identifying such embodied emotions in text remains understudied.
Approach: They propose to extend existing binary embodied emotion dataset with Ekman’s six basic emotion categories.
Outcome: The proposed dataset outperforms existing methods with large language models.

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