AttacksarXiv 2602.09431
Grounding-driven attack: Improving the transferability of encoder-based adversarial attacks to large vision-language models
Propose GDA, which aligns image adversarial perturbations with text-grounded evidence and transfers attacks to vision-language models
- arXiv
- 2602.09431
- Published
- Layer
- Prompt layer
- Setting
- Models and APIs
- Attacker
- No-box (offline transfer)
- Evaluated models
- LLaVA, Qwen2.5-VL, InternVL3 and others10
- AttacksDetection evasion
- TechniqueGradient and representation optimization
- ComponentVision
AbstractGDA aligns perturbations with text-grounded evidence, and the authors say this improves zero-query black-box transferability on heterogeneous LVLMs.
GDA is a zero-query black-box encoder transfer attack for heterogeneous LVLMs.