The product M [1:Nr] ζ results in a weight matrix W , where each row is computed by one slice j = 1, 2, • • • , N r of the tensor: Although such parameterization seems to be straightforward, due to the quadratic size of M [1:Nr] , the parameter size of such parameter adapter is N ζ times larger than the basic encoder-decoder model.
overfitting and expensive computational cost make it infeasible (Bertinetto et al., 2016;Ha et al., 2017).