14shows, for each node in the feature extractor of grSemi-CRFs, its gradient consists of two parts: (1) the gradients back propagated from high layer nodes (i.e., longer segments); and (2) the supervising signals from Semi-CRFs.
the supervision in the objective function is added to each node in grSemi-CRFs.