Before revision:  An extensive experimental evaluation comparing different variants of the model provides an insight into its ability to perform well on the downstream prediction tasks. GraphReach significantly outperforms the current state-of-the-art models and achieves an improvement of up to 31 and 11 percentage points, measured in ROC AUC, for the standard pairwise node classification and link prediction tasks, respectively .
After revision:  An extensive experimental evaluation covering six datasets and five state-of-the-art models and achieves an improvement of up to 31 and 11 percentage points, measured in ROC AUC, for the standard pairwise node classification and link prediction tasks, respectively .