activity
20152022
most citedInteractive Attention Networks for Aspect-Level Sentiment Classification

128 citations · 230 across the 15 of their papers we have counts for

collaborators
Showing 2018Show all

6 papers · 1 filter

cs.CL2018

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…

cs.CL2018

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…

cs.CL2018

SGM: Sequence Generation Model for Multi-label Classification

Pengcheng Yang, Xu Sun, Wei Li +3

Multi-label classification is an important yet challenging task in natural language processing. It is more complex than single-label classification in that the labels tend to be co…

cs.CL2018

Autoencoder as Assistant Supervisor: Improving Text Representation for Chinese Social Media Text Summarization

Shuming Ma, Xu Sun, Junyang Lin +1

Most of the current abstractive text summarization models are based on the sequence-to-sequence model (Seq2Seq). The source content of social media is long and noisy, so it is diff…

cs.CL2018

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…

cs.CL2018

Tag-Enhanced Tree-Structured Neural Networks for Implicit Discourse Relation Classification

Yizhong Wang, Sujian Li, Jingfeng Yang +2

Identifying implicit discourse relations between text spans is a challenging task because it requires understanding the meaning of the text. To tackle this task, recent studies hav…