Improving Single Positive Multi-label Classification with a Generalized Robust Loss Framework

The proposed Generalized Robust Loss (GR Loss) framework can effectively address the challenges of false negatives and class imbalance in Single Positive Multi-label Classification (SPML) by incorporating soft pseudo-labeling and a novel robust loss function.