Distribution of sample label counts in the GoEmotionstraining and testing sets.

<p>Distribution of sample label counts in the GoEmotionstraining and testing sets.</p>

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Bibliographic Details
Main Author:	Jingyi Zhou (3681790) (author)
Other Authors:	Senlin Luo (610842) (author), Haofan Chen (18084565) (author)
Published:	2025
Subjects:	Medicine Sociology Biological Sciences not elsewhere classified Information Systems not elsewhere classified thereby fully leveraging severe label imbalances providing strong support map label values expansion quantization network downstream task completion advancing artificial intelligence emotional intensity representation emotion quantization network rich emotions embedded interdependencies among labels energy intensity levels conducted comparative experiments emotion detection analysis achieve automatic micro eqn framework possesses emotion detection automatic detection emotional reasoning emotion annotation various models substantial subjectivity quantitative research particularly evident manual annotations machine models literature demonstrates level scores learning capabilities high costs high capability goemotions dataset eqn framework crucial foundation comprehensive comparison broad applicability basic comprehension adversely affect
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