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Wenye Li

The Chinese University of Hong Kong, Shenzhen

9 papers hereh-index 12587 citations48 works total

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

author position
  • sole author2
  • first author2
  • middle author3
  • last author2

Across the 9 of 9 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.CL2
  • cs.CV1
  • cs.DC1
  • cs.SI1
affiliations
  • The Chinese University of Hong Kong, Shenzhen
same name
  • Wenye Li — 9 papers, h 4
  • Wenye Li — 4 papers, h 6
  • Wenye Li — 1 paper, 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
20182023
most citedS-NeRF: Neural Radiance Fields for Street Views

13 citations · 20 across the 9 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CL2019★ 3 cited

Sparse Lifting of Dense Vectors: Unifying Word and Sentence Representations

Wenye Li, Senyue Hao

As the first step in automated natural language processing, representing words and sentences is of central importance and has attracted significant research attention. Different ap…

cs.CL2019

An Augmented Transformer Architecture for Natural Language Generation Tasks

Hailiang Li, Adele Y. C. Wang, Yang Liu +3

The Transformer based neural networks have been showing significant advantages on most evaluations of various natural language processing and other sequence-to-sequence tasks due t…

cs.LG2019

Modeling Winner-Take-All Competition in Sparse Binary Projections

Wenye Li

Inspired by the advances in biological science, the study of sparse binary projection models has attracted considerable recent research attention. The models project dense input sa…

cs.LG2019★ 2 cited

AuxBlocks: Defense Adversarial Example via Auxiliary Blocks

Yueyao Yu, Pengfei Yu, Wenye Li

Deep learning models are vulnerable to adversarial examples, which poses an indisputable threat to their applications. However, recent studies observe gradient-masking defenses are…

◍wovepaper

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