activity
20182026
most citedText Compression-aided Transformer Encoding

51 citations · 242 across the 54 of their papers we have counts for

collaborators
Showing 2019Show all

10 papers · 1 filter

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★ 1 cited

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★ 2 cited

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★ 6 cited

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…

cs.CL2019★ 4 cited

Modeling Named Entity Embedding Distribution into Hypersphere

Zhuosheng Zhang, Bingjie Tang, Zuchao Li +1

This work models named entity distribution from a way of visualizing topological structure of embedding space, so that we make an assumption that most, if not all, named entities (…

cs.CL2019★ 24 cited

Semantics-aware BERT for Language Understanding

Zhuosheng Zhang, Yuwei Wu, Hai Zhao +4

The latest work on language representations carefully integrates contextualized features into language model training, which enables a series of success especially in various machi…

cs.CL2019★ 4 cited

Parsing All: Syntax and Semantics, Dependencies and Spans

Junru Zhou, Zuchao Li, Hai Zhao

Both syntactic and semantic structures are key linguistic contextual clues, in which parsing the latter has been well shown beneficial from parsing the former. However, few works e…

cs.CL2019★ 18 cited

Dependency or Span, End-to-End Uniform Semantic Role Labeling

Zuchao Li, Shexia He, Hai Zhao +4

Semantic role labeling (SRL) aims to discover the predicateargument structure of a sentence. End-to-end SRL without syntactic input has received great attention. However, most of t…