Soft-sharing: In our soft-sharing approach, we encourage shared parameters to be close in representation space by penalizing their l 2 distances.
we keep the lower-level layer (i.e., first layer closer to input words) of the 2layer encoder of all three tasks unshared, while we share the higher layer (second layer in our model as shown in Fig.