This network takes the auxiliary task outputs as input.
we define the output label embedding o i of task T i as the sum of the task's label embeddings l j weighted with their probability p T i j : The label embeddings l encode general relationship between labels, while the model's probability distribution p T i over its predictions encodes finegrained information useful for learning (Hinton et al., 2015).