collaborators

5 papers

cs.CV2026

Hierarchical Anti-Aesthetics: Protecting Facial Privacy against Customized Diffusion Models

Songping Wang, Yueming Lyu, Shiqi Liu +5

The rise of customized diffusion models has fueled a boom in personalized visual content creation, but it also introduces serious risks of malicious misuse, thereby posing threats…

cs.CL2026

Understanding the Ability of LLMs to Handle Character-Level Perturbation

Anyuan Zhuo, Xuefei Ning, Ningyuan Li +3

This work investigates the resilience of contemporary large language models (LLMs) against frequent character-level perturbations. We examine three types of character-level perturb…

cs.CV2026

Exposing and Defending the Achilles' Heel of Video Mixture-of-Experts

Songping Wang, Qinglong Liu, Yueming Lyu +3

Mixture-of-Experts (MoE) has demonstrated strong performance in video understanding tasks, yet its adversarial robustness remains underexplored. Existing attack methods often treat…

cs.CV2025

Anti-Aesthetics: Protecting Facial Privacy against Customized Text-to-Image Synthesis

Songping Wang, Yueming Lyu, Shiqi Liu +4

The rise of customized diffusion models has spurred a boom in personalized visual content creation, but also poses risks of malicious misuse, severely threatening personal privacy…

cs.CV2025

Pyramidal Flow Matching for Efficient Video Generative Modeling

Yang Jin, Zhicheng Sun, Ningyuan Li +7

Video generation requires modeling a vast spatiotemporal space, which demands significant computational resources and data usage. To reduce the complexity, the prevailing approache…