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References (100)

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Generalized Transferable Attack Across Datasets
2026Yunxiao Qin, Yuanhao Xiong et al.
[2]
ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers
2025Hanwen Cao, Haobo Lu et al.
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Disrupting Semantic and Abstract Features for Better Adversarial Transferability
2025Yuyang Luo, Xiaosen Wang et al.
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2025Shangbo Wu, Yu-an Tan et al.
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2025Yu Guo, Weiquan Liu et al.
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Attention! Your Vision Language Model Could Be Maliciously Manipulated
2025Xiaosen Wang, Shaokang Wang et al.
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Harnessing the Computation Redundancy in ViTs to Boost Adversarial Transferability
2025Jiani Liu, Zhiyuan Wang et al.
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2025Yuchen Ren, Zhengyu Zhao et al.
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Boosting the Local Invariance for Better Adversarial Transferability
2025Bohan Liu, Xiaosen Wang
[10]
AIM: Additional Image Guided Generation of Transferable Adversarial Attacks
2025Teng Li, Xingjun Ma et al.
[11]
Everywhere Attack: Attacking Locally and Globally to Boost Targeted Transferability
2025Hui Zeng, Sanshuai Cui et al.
[12]
Improving Integrated Gradient-based Transferable Adversarial Examples by Refining the Integration Path
2024Yuchen Ren, Zhengyu Zhao et al.
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2024Yichen Wang, Yu-Cheng Chou et al.
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2024Wenzhuo Xu, Kai Chen et al.
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Improving Adversarial Transferability via Frequency-Guided Sample Relevance Attack
2024Xinyi Wang, Zhibo Jin et al.
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2024Yubo Wang, Chaohu Liu et al.
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ViTH-RFG: Vision Transformer Hashing With Residual Fuzzy Generation for Targeted Attack in Medical Image Retrieval
2024Weiping Ding, Chuansheng Liu et al.
[18]
TrojVLM: Backdoor Attack Against Vision Language Models
2024Weimin Lyu, Lu Pang et al.
[19]
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2024Mingze Sun, Lihua Jing et al.
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Showing 20 of 100 references

Founder's Pitch

"Develop a standardized framework and benchmark for evaluating adversarial transferability in image classification models."

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