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researcher

Yi Zhang

4 papers hereh-index 5159 citations13 works total

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

author position
  • first author2
  • middle author2

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

fields
  • cs.CV2
  • cs.CR1
  • cs.LG1
same name
  • Yi Zhang — 23 papers, h 37
  • Yi Zhang — 18 papers
  • Yi Zhang — 17 papers
  • Yi Zhang — 16 papers
  • Yi Zhang — 16 papers, h 22
  • Yi Zhang — 14 papers

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 citedTowards Accuracy-Fairness Paradox: Adversarial Example-based Data Augmentation for Visual Debiasing

13 citations · 20 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2022★ 5 cited

Zero-shot Image Captioning by Anchor-augmented Vision-Language Space Alignment

Junyang Wang, Yi Zhang, Ming Yan +2

CLIP (Contrastive Language-Image Pre-Training) has shown remarkable zero-shot transfer capabilities in cross-modal correlation tasks such as visual classification and image retriev…

cs.LG2022★ 1 cited

Fair Visual Recognition via Intervention with Proxy Features

Yi Zhang, Jitao Sang, Junyang Wang

Deep learning models often learn to make predictions that rely on sensitive social attributes like gender and race, which poses significant fairness risks, especially in societal a…

cs.CR2022★ 1 cited

Debiasing Backdoor Attack: A Benign Application of Backdoor Attack in Eliminating Data Bias

Shangxi Wu, Qiuyang He, Yi Zhang +1

Backdoor attack is a new AI security risk that has emerged in recent years. Drawing on the previous research of adversarial attack, we argue that the backdoor attack has the potent…

cs.CV2020★ 13 cited

Towards Accuracy-Fairness Paradox: Adversarial Example-based Data Augmentation for Visual Debiasing

Yi Zhang, Jitao Sang

Machine learning fairness concerns about the biases towards certain protected or sensitive group of people when addressing the target tasks. This paper studies the debiasing proble…

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