Qun Liu

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Troy University

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HUAWEI Technologies Co., Ltd.

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Dublin City University

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Institute of Computing Technology, Chinese Academy of Sciences

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ADAPT Centre

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Louisiana State University

Professor at ADAPT Centre - Dublin City University, Professor, Reseacher at Institute of Computing Technology, Chinese Academy of Sciences

research

∙ 08/31/2019

NEZHA: Neural Contextualized Representation for Chinese Language Understanding

The pre-trained language models have achieved great successes in various...

Junqiu Wei, et al. ∙

research

∙ 08/21/2019

Dialog State Tracking with Reinforced Data Augmentation

Neural dialog state trackers are generally limited due to the lack of qu...

Yichun Yin, et al. ∙

research

∙ 08/11/2019

PCGAN-CHAR: Progressively Trained Classifier Generative Adversarial Networks for Classification of Noisy Handwritten Bangla Characters

Due to the sparsity of features, noise has proven to be a great inhibito...

Qun Liu, et al. ∙

research

∙ 07/10/2019

Modeling Semantic Compositionality with Sememe Knowledge

Semantic compositionality (SC) refers to the phenomenon that the meaning...

Fanchao Qi, et al. ∙

research

∙ 06/29/2019

GPT-based Generation for Classical Chinese Poetry

We present a simple yet effective method for generating high quality cla...

Yi Liao, et al. ∙

research

∙ 06/24/2019

Decomposable Neural Paraphrase Generation

Paraphrasing exists at different granularity levels, such as lexical lev...

Zichao Li, et al. ∙

research

∙ 06/06/2019

Bridging the Gap between Training and Inference for Neural Machine Translation

Neural Machine Translation (NMT) generates target words sequentially in ...

Wen Zhang, et al. ∙

research

∙ 05/17/2019

ERNIE: Enhanced Language Representation with Informative Entities

Neural language representation models such as BERT pre-trained on large-...

Zhengyan Zhang, et al. ∙

research

∙ 05/12/2019

Why do you take that route?

The purpose of this paper is to determine whether a particular context f...

Alimire Nabijiang, et al. ∙

research

∙ 04/09/2019

Bilingual-GAN: A Step Towards Parallel Text Generation

Latent space based GAN methods and attention based sequence to sequence ...

Ahmad Rashid, et al. ∙

research

∙ 04/08/2019

Improving Domain Adaptation Translation with Domain Invariant and Specific Information

In domain adaptation for neural machine translation, translation perform...

Shuhao Gu, et al. ∙

research

∙ 03/27/2019

Improving Route Choice Models by Incorporating Contextual Factors via Knowledge Distillation

Route Choice Models predict the route choices of travelers traversing an...

Qun Liu, et al. ∙

research

∙ 11/02/2018

Improving the Robustness of Speech Translation

Although neural machine translation (NMT) has achieved impressive progre...

Xiang Li, et al. ∙

research

∙ 10/15/2018

Learning to Jointly Translate and Predict Dropped Pronouns with a Shared Reconstruction Mechanism

Pronouns are frequently omitted in pro-drop languages, such as Chinese, ...

Longyue Wang, et al. ∙

research

∙ 09/09/2018

Speeding Up Neural Machine Translation Decoding by Cube Pruning

Although neural machine translation has achieved promising results, it s...

Wen Zhang, et al. ∙

research

∙ 06/21/2018

Pixel-level Reconstruction and Classification for Noisy Handwritten Bangla Characters

Classification techniques for images of handwritten characters are susce...

Manohar Karki, et al. ∙

research

∙ 06/05/2018

Understanding Meanings in Multilingual Customer Feedback

Understanding and being able to react to customer feedback is the most f...

Chao-Hong Liu, et al. ∙

research

∙ 05/03/2018

SafeRNet: Safe Transportation Routing in the era of Internet of Vehicles and Mobile Crowd Sensing

World wide road traffic fatality and accident rates are high, and this i...

Qun Liu, et al. ∙

research

∙ 05/02/2018

Unsupervised Learning using Pretrained CNN and Associative Memory Bank

Deep Convolutional features extracted from a comprehensive labeled datas...

Qun Liu, et al. ∙

research

∙ 04/17/2018

Improving Character-based Decoding Using Target-Side Morphological Information for Neural Machine Translation

Recently, neural machine translation (NMT) has emerged as a powerful alt...

Peyman Passban, et al. ∙

research

∙ 01/10/2018

Translating Pro-Drop Languages with Reconstruction Models

Pronouns are frequently omitted in pro-drop languages, such as Chinese, ...

Longyue Wang, et al. ∙

research

∙ 10/17/2017

CASICT Tibetan Word Segmentation System for MLWS2017

We participated in the MLWS 2017 on Tibetan word segmentation task, our ...

Jiawei Hu, et al. ∙

research

∙ 09/12/2017

Refining Source Representations with Relation Networks for Neural Machine Translation

Although neural machine translation (NMT) with the encoder-decoder frame...

Wen Zhang, et al. ∙

research

∙ 09/06/2017

Information-Propogation-Enhanced Neural Machine Translation by Relation Model

Even though sequence-to-sequence neural machine translation (NMT) model ...

Wen Zhang, et al. ∙

research

∙ 05/02/2017

Deep Neural Machine Translation with Linear Associative Unit

Deep Neural Networks (DNNs) have provably enhanced the state-of-the-art ...

Mingxuan Wang, et al. ∙

research

∙ 04/24/2017

Lexically Constrained Decoding for Sequence Generation Using Grid Beam Search

We present Grid Beam Search (GBS), an algorithm which extends beam searc...

Chris Hokamp, et al. ∙

research

∙ 04/14/2017

Exploiting Cross-Sentence Context for Neural Machine Translation

In translation, considering the document as a whole can help to resolve ...

Longyue Wang, et al. ∙

research

∙ 02/04/2017

Doubly-Attentive Decoder for Multi-modal Neural Machine Translation

We introduce a Multi-modal Neural Machine Translation model in which a d...

Iacer Calixto, et al. ∙

research

∙ 02/03/2017

Multilingual Multi-modal Embeddings for Natural Language Processing

We propose a novel discriminative model that learns embeddings from mult...

Iacer Calixto, et al. ∙

research

∙ 01/23/2017

Incorporating Global Visual Features into Attention-Based Neural Machine Translation

We introduce multi-modal, attention-based neural machine translation (NM...

Iacer Calixto, et al. ∙

research

∙ 10/17/2016

Interactive Attention for Neural Machine Translation

Conventional attention-based Neural Machine Translation (NMT) conducts d...

Fandong Meng, et al. ∙

research

∙ 06/07/2016

Memory-enhanced Decoder for Neural Machine Translation

We propose to enhance the RNN decoder in a neural machine translator (NM...

Mingxuan Wang, et al. ∙

research

∙ 05/22/2016

Automatic Construction of Discourse Corpora for Dialogue Translation

In this paper, a novel approach is proposed to automatically construct p...

Longyue Wang, et al. ∙

research

∙ 04/21/2016

A Novel Approach to Dropped Pronoun Translation

Dropped Pronouns (DP) in which pronouns are frequently dropped in the so...

Longyue Wang, et al. ∙

research

∙ 03/12/2016

Variational Neural Discourse Relation Recognizer

Implicit discourse relation recognition is a crucial component for autom...

Biao Zhang, et al. ∙

research

∙ 08/10/2015

Improve the Evaluation of Fluency Using Entropy for Machine Translation Evaluation Metrics

The widely-used automatic evaluation metrics cannot adequately reflect t...

Hui Yu, et al. ∙

research

∙ 08/09/2015

An Automatic Machine Translation Evaluation Metric Based on Dependency Parsing Model

Most of the syntax-based metrics obtain the similarity by comparing the ...

Hui Yu, et al. ∙

research

∙ 06/22/2015

A Deep Memory-based Architecture for Sequence-to-Sequence Learning

We propose DEEPMEMORY, a novel deep architecture for sequence-to-sequenc...

Fandong Meng, et al. ∙

research

∙ 03/17/2015

genCNN: A Convolutional Architecture for Word Sequence Prediction

We propose a novel convolutional architecture, named genCNN, for word se...

Mingxuan Wang, et al. ∙

research

∙ 03/09/2015

Syntax-based Deep Matching of Short Texts

Many tasks in natural language processing, ranging from machine translat...

Mingxuan Wang, et al. ∙

research

∙ 03/06/2015

Encoding Source Language with Convolutional Neural Network for Machine Translation

The recently proposed neural network joint model (NNJM) (Devlin et al., ...

Fandong Meng, et al. ∙

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Qun Liu

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