Before revision:  In  fine-tuning stage, we choose four benchmark downstream tasks, i.e., link prediction, similarity search, node classification and node clustering. We use node sequence pairs as input for link prediction and similarity search, and a single node sequence as input for node classification and clustering. The experimental results of the above taskson four real-world datasetsverify the advancement of PF-HIN , as it outperforms state-of-the-art alternatives consistently and significantly .
After revision:  In fine-tuning stage, we choose four benchmark downstream tasks, i.e., link prediction, similarity search, node classification , and node clustering. PF-HIN , as it outperforms state-of-the-art alternatives consistently and significantly .