Machine reading comprehension (MRC), which requires a machine to answer questions
based on a given context, has attracted increasing attention with the incorporation of various …

It is intuitive that NLP tasks for logographic languages like Chinese should benefit from the
use of the glyph information in those languages. However, due to the lack of rich …

This paper describes the neural dependency parser submitted by Stanford to the CoNLL
2017 Shared Task on parsing Universal Dependencies. Our system uses relatively simple …

Head-driven phrase structure grammar (HPSG) enjoys a uniform formalism representing rich
contextual syntactic and even semantic meanings. This paper makes the first attempt to …

We investigate the problem of efficiently incorporating high-order features into neural graph-
based dependency parsing. Instead of explicitly extracting high-order features from …

In this work, we first analyze the memory behavior in three recurrent neural networks (RNN)
cells; namely, the simple RNN (SRN), the long short-term memory (LSTM) and the gated …

One of the major goals in automated argumentation mining is to uncover the argument
structure present in argumentative text. In order to determine this structure, one must …

We propose a novel transition-based algorithm that straightforwardly parses sentences from
left to right by building $ n $ attachments, with $ n $ being the length of the input sentence …

Both bottom-up and top-down strategies have been used for neural transition-based
constituent parsing. The parsing strategies differ in terms of the order in which they …

Due to the spread of social media-based applications and the challenges posed by the
treatment of social media texts in NLP tools, tailored approaches and ad hoc resources are …