Papers with difficult-to-classify

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PEMV: Improving Spatial Distribution for Emotion Recognition in Conversations Using Proximal Emotion Mean Vectors (2025.findings-naacl)

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Challenge: Existing research focuses on the analysis of contextual structure in dialogue and the interactions between different emotions.
Approach: They propose a method that generates Proximal Emotion Mean Vectors (PEMVs) based on emotion feature queues to optimize the spatial representation of text features.
Outcome: The proposed method achieves state-of-the-art performance on three widely used benchmark datasets.

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