Suppose there’s task $T_1,T_2,..,T_C$, each task has a training set $\{D_{train}^{c}, D_{testing}^{c}\}$, and some of them has larger training set, while some of them have smaller training set. The few shot tasks typically have less training set and are our target task. Multitask learning models are jointly trained on these tasks, i.e., parameters for one task are constrained by other tasks.