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Lei Wang

University of Electronic Science and Technology of China

4 papers hereh-index 223k citations25 works total

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

author position
  • first author1
  • middle author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL3
  • physics.ins-det1
affiliations
  • University of Electronic Science and Technology of China
  • Singapore Management University
Homepage
same name
  • Lei Wang — 25 papers, h 40
  • Lei Wang — 14 papers, h 13
  • Lei Wang — 13 papers
  • Lei Wang — 13 papers, h 22
  • Lei Wang — 13 papers, h 21
  • Lei Wang — 12 papers, h 33

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

most citedMWPToolkit: An Open-Source Framework for Deep Learning-Based Math Word Problem Solvers

20 citations · 22 across the 2 of their papers we have counts for

collaborators

4 papers

cs.CL2021★ 20 cited

MWPToolkit: An Open-Source Framework for Deep Learning-Based Math Word Problem Solvers

Yihuai Lan, Lei Wang, Qiyuan Zhang +5

Developing automatic Math Word Problem (MWP) solvers has been an interest of NLP researchers since the 1960s. Over the last few years, there are a growing number of datasets and de…

cs.CL2021★ 2 cited

DeepStyle: User Style Embedding for Authorship Attribution of Short Texts

Zhiqiang Hu, Roy Ka-Wei Lee, Lei Wang +2

Authorship attribution (AA), which is the task of finding the owner of a given text, is an important and widely studied research topic with many applications. Recent works have sho…

cs.CL2018

Translating a Math Word Problem to an Expression Tree

Lei Wang, Yan Wang, Deng Cai +2

Sequence-to-sequence (SEQ2SEQ) models have been successfully applied to automatic math word problem solving. Despite its simplicity, a drawback still remains: a math word problem c…

physics.ins-det2018

Beyond the N​ limit of the least squares resolution and the lucky model

Gregorio Landi, Giovanni E. Landi

A very simple Gaussian model is used to illustrate a new fitting result: a linear growth of the resolution with the number N of detecting layers. This rule is well beyond the well-…

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