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Guoliang Li

12 papers hereh-index 7206 citations17 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author7
  • last author2

Across the 12 of 12 papers where every author was matched, so the position is known.

fields
  • cs.DB3
  • cs.CL2
  • cs.LG2
  • cs.AI1
  • cs.DC1
  • cs.HC1
same name
  • Guoliang Li — 38 papers, h 12
  • Guoliang Li — 20 papers, h 9
  • Guoliang Li — 17 papers, h 5
  • Guoliang Li — 13 papers, h 68
  • Guoliang Li — 10 papers, h 10
  • Guoliang Li — 8 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20122022
most citednvBench: A Large-Scale Synthesized Dataset for Cross-Domain Natural Language to Visualization Task

11 citations · 30 across the 12 of their papers we have counts for

collaborators
Showing 2021Show all

4 papers · 1 filter

cs.HC2021★ 11 cited

nvBench: A Large-Scale Synthesized Dataset for Cross-Domain Natural Language to Visualization Task

Yuyu Luo, Jiawei Tang, Guoliang Li

NL2VIS - which translates natural language (NL) queries to corresponding visualizations (VIS) - has attracted more and more attention both in commercial visualization vendors and a…

cs.CL2021

Recurrent multiple shared layers in Depth for Neural Machine Translation

GuoLiang Li, Yiyang Li

Learning deeper models is usually a simple and effective approach to improve model performance, but deeper models have larger model parameters and are more difficult to train. To g…

cs.CL2021

Residual Tree Aggregation of Layers for Neural Machine Translation

GuoLiang Li, Yiyang Li

Although attention-based Neural Machine Translation has achieved remarkable progress in recent layers, it still suffers from issue of making insufficient use of the output of each…

eess.SP2021★ 1 cited

Accelerating Edge Intelligence via Integrated Sensing and Communication

Tong Zhang, Shuai Wang, Guoliang Li +3

Realizing edge intelligence consists of sensing, communication, training, and inference stages. Conventionally, the sensing and communication stages are executed sequentially, whic…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.