AI RESEARCH
CMHL: Contrastive Multi-Head Learning for Emotionally Consistent Text Classification
arXiv CS.LG
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ArXi:2603.14078v1 Announce Type: cross Textual Emotion Classification (TEC) is one of the most difficult NLP tasks. State of the art approaches rely on Large language models (LLMs) and multi-model ensembles. In this study, we challenge the assumption that larger scale or complex models are necessary for improved performance. In order to improve logical consistency, We