Appendix: Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative

In this section, we conduct experiments to explore the effect of hyperparameters. There are two important tradeoff parameters α, and β in our proposed method. We select four representative datasets to perform the ablation study. For each data set, when varying one parameter, the other is set as constant. To investigate the effect of α, we search its value in the range of {0.1, 0.2, 0.5, 1.0}. The experimental results are summarized in Table 1. From the table, we can find that α is able to improve the performance in a wide range of hyper-parameters (0.1-0.5).