189 citations · 1.7k across the 110 of their papers we have counts for
14 papers · 1 filter
A Chinese Dataset with Negative Full Forms for General Abbreviation Prediction
Yi Zhang, Xu Sun
Abbreviation is a common phenomenon across languages, especially in Chinese. In most cases, if an expression can be abbreviated, its abbreviation is used more often than its fully…
Complex Structure Leads to Overfitting: A Structure Regularization Decoding Method for Natural Language Processing
Xu Sun, Weiwei Sun, Shuming Ma +4
Recent systems on structured prediction focus on increasing the level of structural dependencies within the model. However, our study suggests that complex structures entail high o…
Deep Stacking Networks for Low-Resource Chinese Word Segmentation with Transfer Learning
Jingjing Xu, Xu Sun, Sujian Li +2
In recent years, neural networks have proven to be effective in Chinese word segmentation. However, this promising performance relies on large-scale training data. Neural networks…
Hybrid Oracle: Making Use of Ambiguity in Transition-based Chinese Dependency Parsing
Xuancheng Ren, Xu Sun
In the training of transition-based dependency parsers, an oracle is used to predict a transition sequence for a sentence and its gold tree. However, the transition system may exhi…
Does Higher Order LSTM Have Better Accuracy for Segmenting and Labeling Sequence Data?
Yi Zhang, Xu Sun, Shuming Ma +2
Existing neural models usually predict the tag of the current token independent of the neighboring tags. The popular LSTM-CRF model considers the tag dependencies between every two…
A Discourse-Level Named Entity Recognition and Relation Extraction Dataset for Chinese Literature Text
Jingjing Xu, Ji Wen, Xu Sun +1
Named Entity Recognition and Relation Extraction for Chinese literature text is regarded as the highly difficult problem, partially because of the lack of tagging sets. In this pap…
Training Simplification and Model Simplification for Deep Learning: A Minimal Effort Back Propagation Method
Xu Sun, Xuancheng Ren, Shuming Ma +5
We propose a simple yet effective technique to simplify the training and the resulting model of neural networks. In back propagation, only a small subset of the full gradient is co…
Label Embedding Network: Learning Label Representation for Soft Training of Deep Networks
Xu Sun, Bingzhen Wei, Xuancheng Ren +1
We propose a method, called Label Embedding Network, which can learn label representation (label embedding) during the training process of deep networks. With the proposed method,…
A Semantic Relevance Based Neural Network for Text Summarization and Text Simplification
Shuming Ma, Xu Sun
Text summarization and text simplification are two major ways to simplify the text for poor readers, including children, non-native speakers, and the functionally illiterate. Text…
Improving Semantic Relevance for Sequence-to-Sequence Learning of Chinese Social Media Text Summarization
Shuming Ma, Xu Sun, Jingjing Xu +3
Current Chinese social media text summarization models are based on an encoder-decoder framework. Although its generated summaries are similar to source texts literally, they have…
meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting
Xu Sun, Xuancheng Ren, Shuming Ma +1
We propose a simple yet effective technique for neural network learning. The forward propagation is computed as usual. In back propagation, only a small subset of the full gradient…
A Generic Online Parallel Learning Framework for Large Margin Models
Shuming Ma, Xu Sun
To speed up the training process, many existing systems use parallel technology for online learning algorithms. However, most research mainly focus on stochastic gradient descent (…
Lock-Free Parallel Perceptron for Graph-based Dependency Parsing
Xu Sun, Shuming Ma
Dependency parsing is an important NLP task. A popular approach for dependency parsing is structured perceptron. Still, graph-based dependency parsing has the time complexity of $O…
Transfer Deep Learning for Low-Resource Chinese Word Segmentation with a Novel Neural Network
Jingjing Xu, Xu Sun
Recent studies have shown effectiveness in using neural networks for Chinese word segmentation. However, these models rely on large-scale data and are less effective for low-resour…