Experimental results on five public datasets from different domains show that combining the base models with HiLAP yields an average performance improvement of 33.4% in Macro-F1 over corresponding flat classifiers and outperforms state-ofthe-art HTC methods by a large margin.
ablation study shows that HiLAP is especially beneficial to those unpopular labels at the bottom levels.