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Bo Yang

4 papers hereh-index 333 citations5 works total

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

author position
  • first author1
  • middle author3

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

fields
  • cs.CV3
  • cs.CR1
same name
  • Bo Yang — 28 papers, h 24
  • Bo Yang — 23 papers, h 8
  • Bo Yang — 22 papers, h 30
  • Bo Yang — 20 papers, h 23
  • Bo Yang — 19 papers, h 8
  • Bo Yang — 15 papers, h 13

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
20242026
collaborators

4 papers

cs.CV2026

On Success and Simplicity: A Second Look at Transferable Vision-Language Attack Pipeline

Yuchen Ren, Zhengyu Zhao, Chenhao Lin +2

Vision-Language Pre-training Models (VLPMs) are known to be vulnerable to adversarial attacks. Recent transferable attacks on VLPMs have followed a common pipeline with complicated…

cs.CV2025

Use as Many Surrogates as You Want: Selective Ensemble Attack to Unleash Transferability without Sacrificing Resource Efficiency

Bo Yang, Hengwei Zhang, Jindong Wang +4

In surrogate ensemble attacks, using more surrogate models yields higher transferability but lower resource efficiency. This practical trade-off between transferability and efficie…

cs.CV2025

Improving Adversarial Transferability on Vision Transformers via Forward Propagation Refinement

Yuchen Ren, Zhengyu Zhao, Chenhao Lin +4

Vision Transformers (ViTs) have been widely applied in various computer vision and vision-language tasks. To gain insights into their robustness in practical scenarios, transferabl…

cs.CR2024

Improving Integrated Gradient-based Transferable Adversarial Examples by Refining the Integration Path

Yuchen Ren, Zhengyu Zhao, Chenhao Lin +4

Transferable adversarial examples are known to cause threats in practical, black-box attack scenarios. A notable approach to improving transferability is using integrated gradients…

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