On the one hand, the guiding-feature method projects the knowledge of the source-side treebank into the target-side treebank, and utilizes extra pattern-based features as guidance for the target-side parsing, mainly for the traditional discrete-feature based parsing .
the multi-task learning method simultaneously trains two parsers on two treebanks and uses shared neural network parameters for representing common-ground syntactic knowledge (Guo et al., 2016).