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20182026
most citedText Compression-aided Transformer Encoding

51 citations · 142 across the 38 of their papers we have counts for

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Showing 2019 · cs.CLShow all

10 papers · 2 filters

cs.CL2019★ 3 cited

Explicit Sentence Compression for Neural Machine Translation

Zuchao Li, Rui Wang, Kehai Chen +4

State-of-the-art Transformer-based neural machine translation (NMT) systems still follow a standard encoder-decoder framework, in which source sentence representation can be well d…

cs.CL2019

Global Greedy Dependency Parsing

Zuchao Li, Hai Zhao, Kevin Parnow

Most syntactic dependency parsing models may fall into one of two categories: transition- and graph-based models. The former models enjoy high inference efficiency with linear time…

cs.CL2019

Dependency and Span, Cross-Style Semantic Role Labeling on PropBank and NomBank

Zuchao Li, Hai Zhao, Junru Zhou +2

The latest developments in neural semantic role labeling (SRL) have shown great performance improvements with both the dependency and span formalisms/styles. Although the two style…

cs.CL2019

Document-level Neural Machine Translation with Associated Memory Network

Shu Jiang, Rui Wang, Zuchao Li +5

Standard neural machine translation (NMT) is on the assumption that the document-level context is independent. Most existing document-level NMT approaches are satisfied with a smat…

cs.CL2019

Subword ELMo

Jiangtong Li, Hai Zhao, Zuchao Li +2

Embedding from Language Models (ELMo) has shown to be effective for improving many natural language processing (NLP) tasks, and ELMo takes character information to compose word rep…

cs.CL2019

Syntax-aware Multilingual Semantic Role Labeling

Shexia He, Zuchao Li, Hai Zhao

Recently, semantic role labeling (SRL) has earned a series of success with even higher performance improvements, which can be mainly attributed to syntactic integration and enhance…