Label-guided Learning for Text Classification
Table 4: Ablation analysis of the LguidedLearn framework. Label-guided (w/o): LguidedLearn without label-guided encoding layer.
['Model', '20NG', 'R8', 'R52', 'Ohsumed', 'MR']
Actually, after removing label-guided layer LguidedLearn is reduced to a BiLSTM-based text classification model. The comparison results (Label-guided (w/o) vs. LguidedLearn) show that the label-guided layer brings huge gains (>5% accuracy improvement), especially on complex task datasets: 20NG, R52, Ohsumed and MR.