self-paced-learning

The paper proposes UASPL, a method that integrates predictive reliability into sample selection for self-paced learning using evidential neural networks, improving classification performance and interpretability.

This paper proposes a plug-and-play module using self-paced curriculum learning to enhance modality balance in multimodal conversational emotion recognition, achieving consistent F1-score improvements on IEMOCAP and MELD datasets.