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NEZHA: Neural Contextualized Representation for Chinese Language Understanding
The pre-trained language models have achieved great successes in various...
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Dialog State Tracking with Reinforced Data Augmentation
Neural dialog state trackers are generally limited due to the lack of qu...
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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...
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Modeling Semantic Compositionality with Sememe Knowledge
Semantic compositionality (SC) refers to the phenomenon that the meaning...
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GPT-based Generation for Classical Chinese Poetry
We present a simple yet effective method for generating high quality cla...
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Decomposable Neural Paraphrase Generation
Paraphrasing exists at different granularity levels, such as lexical lev...
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Bridging the Gap between Training and Inference for Neural Machine Translation
Neural Machine Translation (NMT) generates target words sequentially in ...
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ERNIE: Enhanced Language Representation with Informative Entities
Neural language representation models such as BERT pre-trained on large-...
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Why do you take that route?
The purpose of this paper is to determine whether a particular context f...
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Bilingual-GAN: A Step Towards Parallel Text Generation
Latent space based GAN methods and attention based sequence to sequence ...
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Improving Domain Adaptation Translation with Domain Invariant and Specific Information
In domain adaptation for neural machine translation, translation perform...
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Improving Route Choice Models by Incorporating Contextual Factors via Knowledge Distillation
Route Choice Models predict the route choices of travelers traversing an...
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Improving the Robustness of Speech Translation
Although neural machine translation (NMT) has achieved impressive progre...
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Learning to Jointly Translate and Predict Dropped Pronouns with a Shared Reconstruction Mechanism
Pronouns are frequently omitted in pro-drop languages, such as Chinese, ...
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Speeding Up Neural Machine Translation Decoding by Cube Pruning
Although neural machine translation has achieved promising results, it s...
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Pixel-level Reconstruction and Classification for Noisy Handwritten Bangla Characters
Classification techniques for images of handwritten characters are susce...
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Understanding Meanings in Multilingual Customer Feedback
Understanding and being able to react to customer feedback is the most f...
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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...
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Unsupervised Learning using Pretrained CNN and Associative Memory Bank
Deep Convolutional features extracted from a comprehensive labeled datas...
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Improving Character-based Decoding Using Target-Side Morphological Information for Neural Machine Translation
Recently, neural machine translation (NMT) has emerged as a powerful alt...
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Translating Pro-Drop Languages with Reconstruction Models
Pronouns are frequently omitted in pro-drop languages, such as Chinese, ...
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CASICT Tibetan Word Segmentation System for MLWS2017
We participated in the MLWS 2017 on Tibetan word segmentation task, our ...
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Refining Source Representations with Relation Networks for Neural Machine Translation
Although neural machine translation (NMT) with the encoder-decoder frame...
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Information-Propogation-Enhanced Neural Machine Translation by Relation Model
Even though sequence-to-sequence neural machine translation (NMT) model ...
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Deep Neural Machine Translation with Linear Associative Unit
Deep Neural Networks (DNNs) have provably enhanced the state-of-the-art ...
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Lexically Constrained Decoding for Sequence Generation Using Grid Beam Search
We present Grid Beam Search (GBS), an algorithm which extends beam searc...
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Exploiting Cross-Sentence Context for Neural Machine Translation
In translation, considering the document as a whole can help to resolve ...
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Doubly-Attentive Decoder for Multi-modal Neural Machine Translation
We introduce a Multi-modal Neural Machine Translation model in which a d...
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Multilingual Multi-modal Embeddings for Natural Language Processing
We propose a novel discriminative model that learns embeddings from mult...
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Incorporating Global Visual Features into Attention-Based Neural Machine Translation
We introduce multi-modal, attention-based neural machine translation (NM...
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Interactive Attention for Neural Machine Translation
Conventional attention-based Neural Machine Translation (NMT) conducts d...
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Memory-enhanced Decoder for Neural Machine Translation
We propose to enhance the RNN decoder in a neural machine translator (NM...
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Automatic Construction of Discourse Corpora for Dialogue Translation
In this paper, a novel approach is proposed to automatically construct p...
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A Novel Approach to Dropped Pronoun Translation
Dropped Pronouns (DP) in which pronouns are frequently dropped in the so...
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Variational Neural Discourse Relation Recognizer
Implicit discourse relation recognition is a crucial component for autom...
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Improve the Evaluation of Fluency Using Entropy for Machine Translation Evaluation Metrics
The widely-used automatic evaluation metrics cannot adequately reflect t...
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An Automatic Machine Translation Evaluation Metric Based on Dependency Parsing Model
Most of the syntax-based metrics obtain the similarity by comparing the ...
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A Deep Memory-based Architecture for Sequence-to-Sequence Learning
We propose DEEPMEMORY, a novel deep architecture for sequence-to-sequenc...
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genCNN: A Convolutional Architecture for Word Sequence Prediction
We propose a novel convolutional architecture, named genCNN, for word se...
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Syntax-based Deep Matching of Short Texts
Many tasks in natural language processing, ranging from machine translat...
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Encoding Source Language with Convolutional Neural Network for Machine Translation
The recently proposed neural network joint model (NNJM) (Devlin et al., ...
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