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Qian Wang

4 papers hereh-index 598 citations11 works total

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

author position
  • middle author1
  • last author3

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

fields
  • cs.CV3
  • cs.CR1
same name
  • Qian Wang — 49 papers, h 21
  • Qian Wang — 27 papers, h 43
  • Qian Wang — 22 papers, h 10
  • Qian Wang — 21 papers, h 12
  • Qian Wang — 18 papers, h 35
  • Qian Wang — 13 papers, h 11

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 citedRevisiting Adversarial Training under Long-Tailed Distributions

2 citations · 2 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2026

VOID: Defeating Unauthorized Mimicry in Latent Diffusion Models

Chunlin Qiu, Ang Li, Tianxiao Huang +7

While Latent Diffusion Models (LDMs) have revolutionized visual synthesis, they are increasingly exploited for unauthorized mimicry of individuals. Existing defenses inject decepti…

cs.CR2024

Zero-Query Adversarial Attack on Black-box Automatic Speech Recognition Systems

Zheng Fang, Tao Wang, Lingchen Zhao +6

In recent years, extensive research has been conducted on the vulnerability of ASR systems, revealing that black-box adversarial example attacks pose significant threats to real-wo…

cs.CV2024

Boosting Adversarial Transferability with Low-Cost Optimization via Maximin Expected Flatness

Chunlin Qiu, Ang Li, Yiheng Duan +4

Transfer-based attacks craft adversarial examples on white-box surrogate models and directly deploy them against black-box target models, offering model-agnostic and query-free thr…

cs.CV2024★ 2 cited

Revisiting Adversarial Training under Long-Tailed Distributions

Xinli Yue, Ningping Mou, Qian Wang +1

Deep neural networks are vulnerable to adversarial attacks, often leading to erroneous outputs. Adversarial training has been recognized as one of the most effective methods to cou…

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