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Shangwei Guo

13 papers hereh-index 201.8k citations78 works total

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

author position
  • first author1
  • middle author12

Across the 13 of 13 papers where every author was matched, so the position is known.

fields
  • cs.CR5
  • cs.CV4
  • cs.AI2
  • cs.CL1
  • cs.LG1
same name
  • Shangwei Guo — 4 papers
  • Shangwei Guo — 4 papers, h 2
  • Shangwei Guo — 3 papers, h 10

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
20202025
most citedBadPre: Task-agnostic Backdoor Attacks to Pre-trained NLP Foundation Models

33 citations · 71 across the 10 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2023

Warfare:Breaking the Watermark Protection of AI-Generated Content

Guanlin Li, Yifei Chen, Jie Zhang +5

AI-Generated Content (AIGC) is rapidly expanding, with services using advanced generative models to create realistic images and fluent text. Regulating such content is crucial to p…

cs.CV2023

What can Discriminator do? Towards Box-free Ownership Verification of Generative Adversarial Network

Ziheng Huang, Boheng Li, Yan Cai +5

In recent decades, Generative Adversarial Network (GAN) and its variants have achieved unprecedented success in image synthesis. However, well-trained GANs are under the threat of…

cs.CV2021★ 12 cited

Local Black-box Adversarial Attacks: A Query Efficient Approach

Tao Xiang, Hangcheng Liu, Shangwei Guo +2

Adversarial attacks have threatened the application of deep neural networks in security-sensitive scenarios. Most existing black-box attacks fool the target model by interacting wi…

cs.CV2020★ 4 cited

Privacy-preserving Collaborative Learning with Automatic Transformation Search

Wei Gao, Shangwei Guo, Tianwei Zhang +3

Collaborative learning has gained great popularity due to its benefit of data privacy protection: participants can jointly train a Deep Learning model without sharing their trainin…

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