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Juncai He

24 papers hereh-index 11716 citations28 works total

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

author position
  • sole author1
  • first author14
  • middle author6
  • last author2

Across the 23 of 24 papers where every author was matched, so the position is known.

fields
  • cs.LG11
  • math.NA7
  • cs.CL2
  • cs.CV2
  • cs.AI1
  • eess.IV1
same name
  • Juncai He — 4 papers, h 3
  • Juncai He — 2 papers, h 2
  • Juncai He — 1 paper

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
20182026
most citedReLU Deep Neural Networks and Linear Finite Elements

155 citations · 379 across the 24 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.CL2024

Alignment at Pre-training! Towards Native Alignment for Arabic LLMs

Juhao Liang, Zhenyang Cai, Jianqing Zhu +9

The alignment of large language models (LLMs) is critical for developing effective and safe language models. Traditional approaches focus on aligning models during the instruction…

cs.CL2024★ 1 cited

Second Language (Arabic) Acquisition of LLMs via Progressive Vocabulary Expansion

Jianqing Zhu, Huang Huang, Zhihang Lin +18

This paper addresses the critical need for democratizing large language models (LLM) in the Arab world, a region that has seen slower progress in developing models comparable to st…

cs.LG2024★ 3 cited

Expressivity and Approximation Properties of Deep Neural Networks with ReLUk Activation

Juncai He, Tong Mao, Jinchao Xu

In this paper, we investigate the expressivity and approximation properties of deep neural networks employing the ReLUk activation function for k≥2. Although deep ReLU ne…

math.NA2024★ 2 cited

Deep Neural Networks and Finite Elements of Any Order on Arbitrary Dimensions

Juncai He, Jinchao Xu

In this study, we establish that deep neural networks employing ReLU and ReLU2 activation functions can effectively represent Lagrange finite element functions of any order on v…

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