Both of these are initialized to zero vectors and recursively updated during traversal, i.e., as nodes are selected for expansion (and hence added to the predicted tag set).
more specifically, the context vector that informs the decision to expand node v in the label hierarchy from its parent node n is a weighted sum of the encoder hidden states h, where weights reflect induced attention over inputs, conditioned on n. : where and a is a simple multi-layer perceptron (mLP), with node-specific parameters θ n .