Cross-lingual Dependency Parsing with Unlabeled Auxiliary Languages
Table 3: Cross-lingual transfer results (UAS%/LAS%, excluding punctuation) of the RNN-Stack parser on the test sets. ‘†’ indicates that the adversarially trained model results are statistically significantly better (by permutation test, p < 0.05) than the model trained only on the source language (en).
['Lang', '(en)', '(en-fr)', '(en-ru)']
Similar to the “SelfAtt-Graph”parser, the “RNN-Stack” parser resulted in significant improvements in cross-lingual transfer from unsupervised language adaptation. We discuss our detailed experimental analysis in the following.