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20242026
most citedModel Inversion Attacks Through Target-Specific Conditional Diffusion Models

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI2026

HASTE: Evolving Agent Harnesses Against Emerging Attacks Using Sparse Evidence

Xiqiao Xiong, Moxin Li, Zhixin Ma +4

Agent harnesses play a critical role in defenses by enforcing safety constraints to prevent unsafe actions. However, rapidly emerging attacks outpace manual harness adaptation, mot…

cs.CV2025

Easier Painting Than Thinking: Can Text-to-Image Models Set the Stage, but Not Direct the Play?

Ouxiang Li, Yuan Wang, Xinting Hu +7

Text-to-image (T2I) generation aims to synthesize images from textual prompts, which jointly specify what must be shown and imply what can be inferred, which thus correspond to two…

cs.CV2025

SPEED: Scalable, Precise, and Efficient Concept Erasure for Diffusion Models

Ouxiang Li, Yuan Wang, Xinting Hu +3

Erasing concepts from large-scale text-to-image (T2I) diffusion models has become increasingly crucial due to the growing concerns over copyright infringement, offensive content, a…

cs.CV2024

Improving Synthetic Image Detection Towards Generalization: An Image Transformation Perspective

Ouxiang Li, Jiayin Cai, Yanbin Hao +3

With recent generative models facilitating photo-realistic image synthesis, the proliferation of synthetic images has also engendered certain negative impacts on social platforms,…

cs.CV2024★ 2 cited

Model Inversion Attacks Through Target-Specific Conditional Diffusion Models

Ouxiang Li, Yanbin Hao, Zhicai Wang +4

Model inversion attacks (MIAs) aim to reconstruct private images from a target classifier's training set, thereby raising privacy concerns in AI applications. Previous GAN-based MI…