FLHG addresses label sparsity in heterogeneous graphs through few-shot learning methods.
FLHG aims to address label sparsity in heterogeneous graphs by developing methods for effective few-shot learning, categorizing into single-heterogeneity, dual-heterogeneity, and multi-heterogeneity scenarios.