Same Representation, Different Attentions:A New Scheme of Information Sharing for Multi-task Learning
Table 4: Average precision of multi-task models with auxiliary tasks.
['[EMPTY]', 'SSP-MTL', 'PSP-MTL', 'SA-MTL', 'DA-MTL']
We use the same hyperparameters and training procedure as the former experiments. The result shows that by leveraging auxiliary tasks, the performances of SA-MTL and DA-MTL achieve more improvement than PSP-MTL and SSP-MTL.