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researcher

Wei Huang

University of Science and Technology of China

4 papers hereh-index 201.5k citations68 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.CL1
  • cs.CV1
  • cs.IR1
  • cs.LG1
affiliations
  • University of Science and Technology of China
ORCID 0000-0001-7513-3105
same name
  • Wei Huang — 11 papers, h 14
  • Wei Huang — 7 papers
  • Wei Huang — 6 papers
  • Wei Huang — 4 papers
  • Wei Huang — 4 papers
  • Wei Huang — 3 papers, h 4

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
20212023
most citedSelf-Supervised Neuron Segmentation with Multi-Agent Reinforcement Learning

27 citations · 36 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2023★ 27 cited

Self-Supervised Neuron Segmentation with Multi-Agent Reinforcement Learning

Yinda Chen, Wei Huang, Shenglong Zhou +2

The performance of existing supervised neuron segmentation methods is highly dependent on the number of accurate annotations, especially when applied to large scale electron micros…

cs.IR2022★ 2 cited

VLSNR:Vision-Linguistics Coordination Time Sequence-aware News Recommendation

Songhao Han, Wei Huang, Xiaotian Luan

News representation and user-oriented modeling are both essential for news recommendation. Most existing methods are based on textual information but ignore the visual information…

cs.LG2022★ 7 cited

Auto-scaling Vision Transformers without Training

Wuyang Chen, Wei Huang, Xianzhi Du +3

This work targets automated designing and scaling of Vision Transformers (ViTs). The motivation comes from two pain spots: 1) the lack of efficient and principled methods for desig…

cs.CL2021

Improving Cross-Lingual Reading Comprehension with Self-Training

Wei-Cheng Huang, Chien-yu Huang, Hung-yi Lee

Substantial improvements have been made in machine reading comprehension, where the machine answers questions based on a given context. Current state-of-the-art models even surpass…

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