Abstract: Highlights•A multi-teacher approach mitigates unreliable guidance and diversifies learning.•Perturb the feature space via Virtual Adversarial Training to improve generalization.•A novel hybrid loss to address over-regularization and balanced consistency learning.•Comprehensive evaluation and ablation studies on two multi-class benchmark datasets.
External IDs:dblp:journals/cmpb/QiuML25
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