Training a high-accuracy dependency parser requires a large treebank. However, these are
costly and time-consuming to build. We propose a learning method that needs less data …

Recent advances in multilingual dependency parsing have brought the idea of a truly
universal parser closer to reality. However, cross-language interference and restrained …

Linguistic typology aims to capture structural and semantic variation across the world's
languages. A large-scale typology could provide excellent guidance for multilingual Natural …

Different languages might have different word orders. In this paper, we investigate cross-
lingual transfer and posit that an order-agnostic model will perform better when transferring …

Universal Dependencies is a recent initiative to develop cross-linguistically consistent
treebank annotation for many languages, with the goal of facilitating multilingual parser …

One central mystery of neural NLP is what neural models" know" about their subject matter.
When a neural machine translation system learns to translate from one language to another …

This paper proposes to learn languageindependent word representations to address cross-
lingual dependency parsing, which aims to predict the dependency parsing trees for …

We introduce two first-order graph-based dependency parsers achieving a new state of the
art. The first is a consensus parser built from an ensemble of independently trained greedy …

Accurate multilingual transfer parsing typically relies on careful feature engineering. In this
paper, we propose a hierarchical tensor-based approach for this task. This approach …

Cross-lingual transfer learning has become an important weapon to battle the unavailability
of annotated resources for low-resource languages. One of the fundamental techniques to …