Question about Predicted Label Dimensions and the Usages of Test Node Label

[YanJiangJerry]

Thanks for your great work, I have a quick question regarding label dimension and Figure 3 in your paper. In the inductive attention mechanism, the t×c dimension—does the c-dimension correspond to the label dimension of the training set or the test set? Additionally, how does the Linear GNN trained on the training set ensure that the output matches the label dimension of the test set if the label dimension is not consistent, such as training on cora and inference on arxiv? I understand the label-permutation invariance of the distance of LinearGNN predictions, but how can the linearGNN predict the exact test label dimension without any labelled test data? Does GraphAny need to use some test node labels to get the W for linearGNN?
Thanks in advance.