Zero-shot Reading Comprehension by Cross-lingual Transfer Learning with Multi-lingual Language Representation Model
Table 6: EM/F1 scores over artificially created typology-manipulated dataset.
['Train/Test', 'English', 'Chinese', 'Korean']
The results show that the typology manipulation on the training set has little influence. It is possible that multi-BERT normalizes the typology order of different languages to some extent.