A self-paced curriculum learning module with dual-level difficulty scoring improves weighted F1 scores by 1.2-10.4% when added to existing multimodal emotion recognition models on IEMOCAP and MELD.
In: The Forty-first International Conference on Machine 32 Learning (2024)
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Leveraging Self-Paced Curriculum Learning for Enhanced Modality Balance in Multimodal Conversational Emotion Recognition
A self-paced curriculum learning module with dual-level difficulty scoring improves weighted F1 scores by 1.2-10.4% when added to existing multimodal emotion recognition models on IEMOCAP and MELD.