The WEIGHT adaptation technique is not feasible when the source data is smaller than the target data, and the LININT technique performs poorly, as it assigns too much importance the smaller and out-of-domain dataset.
we do see marginal improvements using ALL and AUGMENT, reflecting the value of increasing the training set size by roughly 10%.