activity
20172020
most citedCharacter Composition Model with Convolutional Neural Networks for Dependency Parsing on Morphologically Rich Languages

14 citations · 20 across the 2 of their papers we have counts for

collaborators

5 papers

math.NT2020

On sums of coefficients of Borwein type polynomials over arithmetic progressions

Jiyou Li, Xiang Yu

We obtain asymptotic formulas for sums over arithmetic progressions of coefficients of polynomials of the form where is an odd…

math.DS2020

On Periodic orbits of the Planar N-body Problem

Xiang Yu

By introducing a new coordinate system, we prove that there are abundant new periodic orbits near relative equilibrium solutions of the N-body problem. We consider only Lagrange re…

cs.CL2018

Comparing Attention-based Convolutional and Recurrent Neural Networks: Success and Limitations in Machine Reading Comprehension

Matthias Blohm, Glorianna Jagfeld, Ekta Sood +2

We propose a machine reading comprehension model based on the compare-aggregate framework with two-staged attention that achieves state-of-the-art results on the MovieQA question a…

cs.CL20176 cited

A General-Purpose Tagger with Convolutional Neural Networks

Xiang Yu, Agnieszka Faleńska, Ngoc Thang Vu

We present a general-purpose tagger based on convolutional neural networks (CNN), used for both composing word vectors and encoding context information. The CNN tagger is robust ac…

cs.CL201714 cited

Character Composition Model with Convolutional Neural Networks for Dependency Parsing on Morphologically Rich Languages

Xiang Yu, Ngoc Thang Vu

We present a transition-based dependency parser that uses a convolutional neural network to compose word representations from characters. The character composition model shows grea…