Adversarial Neural Networks for Cross-lingual Sequence Tagging
Table 4: es→fr SC with adversarial training.
['Training data', 'No ADA', 'GR', 'GAN', 'WGAN']
Cross-lingual models. Next, we train cross-lingual models ( Even without adversarial training, the models perform better than the monolingual models. This shows that information can already be shared from ES to FR by using bilingual word embeddings. When adding adversarial training, we again notice a better performance of GR compared to GAN or WGAN: GR training boosts the results, especially for no or little FR training data. GAN and WGAN loss does not perform as good as for dependency parsing.