110 citations · 867 across the 51 of their papers we have counts for
14 papers · 1 filter
Evaluating Semantic Rationality of a Sentence: A Sememe-Word-Matching Neural Network based on HowNet
Shu Liu, Jingjing Xu, Xuancheng Ren +1
Automatic evaluation of semantic rationality is an important yet challenging task, and current automatic techniques cannot well identify whether a sentence is semantically rational…
simNet: Stepwise Image-Topic Merging Network for Generating Detailed and Comprehensive Image Captions
Fenglin Liu, Xuancheng Ren, Yuanxin Liu +2
The encode-decoder framework has shown recent success in image captioning. Visual attention, which is good at detailedness, and semantic attention, which is good at comprehensivene…
A Skeleton-Based Model for Promoting Coherence Among Sentences in Narrative Story Generation
Jingjing Xu, Xuancheng Ren, Yi Zhang +3
Narrative story generation is a challenging problem because it demands the generated sentences with tight semantic connections, which has not been well studied by most existing gen…
Learning When to Concentrate or Divert Attention: Self-Adaptive Attention Temperature for Neural Machine Translation
Junyang Lin, Xu Sun, Xuancheng Ren +2
Most of the Neural Machine Translation (NMT) models are based on the sequence-to-sequence (Seq2Seq) model with an encoder-decoder framework equipped with the attention mechanism. H…
Review-Driven Multi-Label Music Style Classification by Exploiting Style Correlations
Guangxiang Zhao, Jingjing Xu, Qi Zeng +1
This paper explores a new natural language processing task, review-driven multi-label music style classification. This task requires the system to identify multiple styles of music…
Sememe Prediction: Learning Semantic Knowledge from Unstructured Textual Wiki Descriptions
Wei Li, Xuancheng Ren, Damai Dai +3
Huge numbers of new words emerge every day, leading to a great need for representing them with semantic meaning that is understandable to NLP systems. Sememes are defined as the mi…
Deconvolution-Based Global Decoding for Neural Machine Translation
Junyang Lin, Xu Sun, Xuancheng Ren +3
A great proportion of sequence-to-sequence (Seq2Seq) models for Neural Machine Translation (NMT) adopt Recurrent Neural Network (RNN) to generate translation word by word following…
A Hierarchical End-to-End Model for Jointly Improving Text Summarization and Sentiment Classification
Shuming Ma, Xu Sun, Junyang Lin +1
Text summarization and sentiment classification both aim to capture the main ideas of the text but at different levels. Text summarization is to describe the text within a few sent…
Regularizing Output Distribution of Abstractive Chinese Social Media Text Summarization for Improved Semantic Consistency
Bingzhen Wei, Xuancheng Ren, Xu Sun +3
Abstractive text summarization is a highly difficult problem, and the sequence-to-sequence model has shown success in improving the performance on the task. However, the generated…
Unpaired Sentiment-to-Sentiment Translation: A Cycled Reinforcement Learning Approach
Jingjing Xu, Xu Sun, Qi Zeng +4
The goal of sentiment-to-sentiment "translation" is to change the underlying sentiment of a sentence while keeping its content. The main challenge is the lack of parallel data. To…
Query and Output: Generating Words by Querying Distributed Word Representations for Paraphrase Generation
Shuming Ma, Xu Sun, Wei Li +3
Most recent approaches use the sequence-to-sequence model for paraphrase generation. The existing sequence-to-sequence model tends to memorize the words and the patterns in the tra…
Structure Regularized Neural Network for Entity Relation Classification for Chinese Literature Text
Ji Wen, Xu Sun, Xuancheng Ren +1
Relation classification is an important semantic processing task in the field of natural language processing. In this paper, we propose the task of relation classification for Chin…
DP-GAN: Diversity-Promoting Generative Adversarial Network for Generating Informative and Diversified Text
Jingjing Xu, Xuancheng Ren, Junyang Lin +1
Existing text generation methods tend to produce repeated and "boring" expressions. To tackle this problem, we propose a new text generation model, called Diversity-Promoting Gener…
Building an Ellipsis-aware Chinese Dependency Treebank for Web Text
Xuancheng Ren, Xu Sun, Ji Wen +3
Web 2.0 has brought with it numerous user-produced data revealing one's thoughts, experiences, and knowledge, which are a great source for many tasks, such as information extractio…