Yuehuan He

SIAST: A Slot Imbalance-Aware Self-Training Scheme for Semi-Supervised Slot Filling

Slot filling where labelled data are scarce could leverage the recent advances in self-training methods. However, existing self-training models ignore the prevalent imbalanced slot distribution problem in many slot filling datasets. These methods could exacerbate label imbalance during learning iter…