b'Qun Liu'

research

∙ 08/31/2019

NEZHA: Neural Contextualized Representation for Chinese Language Understanding

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

0 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...

5 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...

0 Qun Liu, et al. ∙

research

∙ 07/10/2019

Modeling Semantic Compositionality with Sememe Knowledge

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

0 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...

2 Yi Liao, et al. ∙

research

∙ 06/24/2019

Decomposable Neural Paraphrase Generation

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

0 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 ...

5 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-...

0 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...

0 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 ...

0 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...

0 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...

4 Qun Liu, et al. ∙

research

∙ 11/02/2018

Improving the Robustness of Speech Translation

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

0 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, ...

0 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...

0 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...

0 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...

0 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...

0 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...

0 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...

0 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, ...

0 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 ...

0 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...

0 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 ...

0 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 ...

0 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...

0 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 ...

0 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...

0 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...

0 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...

0 Iacer Calixto, et al. ∙

research

∙ 10/17/2016

Interactive Attention for Neural Machine Translation

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

0 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...

0 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...

0 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...

0 Longyue Wang, et al. ∙

research

∙ 03/12/2016

Variational Neural Discourse Relation Recognizer

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

0 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...

0 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 ...

0 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...

0 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...

0 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...

0 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., ...

0 Fandong Meng, et al. ∙

Qun Liu

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