101 citations · 573 across the 65 of their papers we have counts for
14 papers · 1 filter
Leveraging Dependency Forest for Neural Medical Relation Extraction
Linfeng Song, Yue Zhang, Daniel Gildea +3
Medical relation extraction discovers relations between entity mentions in text, such as research articles. For this task, dependency syntax has been recognized as a crucial source…
Evaluating Commonsense in Pre-trained Language Models
Xuhui Zhou, Yue Zhang, Leyang Cui +1
Contextualized representations trained over large raw text data have given remarkable improvements for NLP tasks including question answering and reading comprehension. There have…
How Can BERT Help Lexical Semantics Tasks?
Yile Wang, Leyang Cui, Yue Zhang
Contextualized embeddings such as BERT can serve as strong input representations to NLP tasks, outperforming their static embeddings counterparts such as skip-gram, CBOW and GloVe.…
Making the Best Use of Review Summary for Sentiment Analysis
Sen Yang, Leyang Cui, Jun Xie +1
Sentiment analysis provides a useful overview of customer review contents. Many review websites allow a user to enter a summary in addition to a full review. Intuitively, summary i…
Contrastive Attention Mechanism for Abstractive Sentence Summarization
Xiangyu Duan, Hoongfei Yu, Mingming Yin +3
We propose a contrastive attention mechanism to extend the sequence-to-sequence framework for abstractive sentence summarization task, which aims to generate a brief summary of a g…
Duality Regularization for Unsupervised Bilingual Lexicon Induction
Xuefeng Bai, Yue Zhang, Hailong Cao +1
Unsupervised bilingual lexicon induction naturally exhibits duality, which results from symmetry in back-translation. For example, EN-IT and IT-EN induction can be mutually primal…
Hierarchically-Refined Label Attention Network for Sequence Labeling
Leyang Cui, Yue Zhang
CRF has been used as a powerful model for statistical sequence labeling. For neural sequence labeling, however, BiLSTM-CRF does not always lead to better results compared with BiLS…
Investigating Self-Attention Network for Chinese Word Segmentation
Leilei Gan, Yue Zhang
Neural network has become the dominant method for Chinese word segmentation. Most existing models cast the task as sequence labeling, using BiLSTM-CRF for representing the input an…
Latent Variable Sentiment Grammar
Liwen Zhang, Kewei Tu, Yue Zhang
Neural models have been investigated for sentiment classification over constituent trees. They learn phrase composition automatically by encoding tree structures but do not explici…
Learning Word Embeddings with Domain Awareness
Guoyin Wang, Yan Song, Yue Zhang +1
Word embeddings are traditionally trained on a large corpus in an unsupervised setting, with no specific design for incorporating domain knowledge. This can lead to unsatisfactory…
Does It Make Sense? And Why? A Pilot Study for Sense Making and Explanation
Cunxiang Wang, Shuailong Liang, Yue Zhang +2
Introducing common sense to natural language understanding systems has received increasing research attention. It remains a fundamental question on how to evaluate whether a system…
Improving Cross-Domain Chinese Word Segmentation with Word Embeddings
Yuxiao Ye, Yue Zhang, Weikang Li +2
Cross-domain Chinese Word Segmentation (CWS) remains a challenge despite recent progress in neural-based CWS. The limited amount of annotated data in the target domain has been the…
Domain Representation for Knowledge Graph Embedding
Cunxiang Wang, Feiliang Ren, Zhichao Lin +3
Embedding entities and relations into a continuous multi-dimensional vector space have become the dominant method for knowledge graph embedding in representation learning. However,…
Semantic Neural Machine Translation using AMR
Linfeng Song, Daniel Gildea, Yue Zhang +2
It is intuitive that semantic representations can be useful for machine translation, mainly because they can help in enforcing meaning preservation and handling data sparsity (many…