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20132021
most citedRevisiting Pre-Trained Models for Chinese Natural Language Processing

565 citations · 3k across the 108 of their papers we have counts for

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Showing 2016Show all

12 papers · 1 filter

cs.CL2016★ 1 cited

Truth Discovery with Memory Network

Luyang Li, Bing Qin, Wenjing Ren +1

Truth discovery is to resolve conflicts and find the truth from multiple-source statements. Conventional methods mostly research based on the mutual effect between the reliability…

cs.SI2016★ 71 cited

A General Framework for Content-enhanced Network Representation Learning

Xiaofei Sun, Jiang Guo, Xiao Ding +1

This paper investigates the problem of network embedding, which aims at learning low-dimensional vector representation of nodes in networks. Most existing network embedding methods…

cs.CL2016★ 9 cited

Learning to Start for Sequence to Sequence Architecture

Qingfu Zhu, Weinan Zhang, Lianqiang Zhou +1

The sequence to sequence architecture is widely used in the response generation and neural machine translation to model the potential relationship between two sentences. It typical…

cs.CL2016★ 171 cited

Attention-over-Attention Neural Networks for Reading Comprehension

Yiming Cui, Zhipeng Chen, Si Wei +3

Cloze-style queries are representative problems in reading comprehension. Over the past few months, we have seen much progress that utilizing neural network approach to solve Cloze…

cs.CL2016★ 34 cited

Consensus Attention-based Neural Networks for Chinese Reading Comprehension

Yiming Cui, Ting Liu, Zhipeng Chen +2

Reading comprehension has embraced a booming in recent NLP research. Several institutes have released the Cloze-style reading comprehension data, and these have greatly accelerated…

cs.CL2016★ 15 cited

Exploiting Multi-typed Treebanks for Parsing with Deep Multi-task Learning

Jiang Guo, Wanxiang Che, Haifeng Wang +1

Various treebanks have been released for dependency parsing. Despite that treebanks may belong to different languages or have different annotation schemes, they contain syntactic k…