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20182026
most citedASTRAL: Adversarial Trained LSTM-CNN for Named Entity Recognition

73 citations · 259 across the 14 of their papers we have counts for

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Showing cs.CLShow all

3 papers · 1 filter

cs.CL2020★ 7 cited

SRQA: Synthetic Reader for Factoid Question Answering

Jiuniu Wang, Wenjia Xu, Xingyu Fu +5

The question answering system can answer questions from various fields and forms with deep neural networks, but it still lacks effective ways when facing multiple evidences. We int…

cs.CL2020★ 73 cited

ASTRAL: Adversarial Trained LSTM-CNN for Named Entity Recognition

Jiuniu Wang, Wenjia Xu, Xingyu Fu +2

Named Entity Recognition (NER) is a challenging task that extracts named entities from unstructured text data, including news, articles, social comments, etc. The NER system has be…

cs.CL2018

A3Net: Adversarial-and-Attention Network for Machine Reading Comprehension

Jiuniu Wang, Xingyu Fu, Guangluan Xu +4

In this paper, we introduce Adversarial-and-attention Network (A3Net) for Machine Reading Comprehension. This model extends existing approaches from two perspectives. First, advers…