collaborators

15 papers

cs.CV2026

TrajShield: Trajectory-Level Safety Mediation for Defending Text-to-Video Models Against Jailbreak Attacks

Quanchen Zou, Nizhang Li, Wenxin Zhang +4

Text-to-Video (T2V) models have demonstrated remarkable capability in generating temporally coherent videos from natural language prompts, yet they also risk producing unsafe conte…

cs.CR2026

AgentVisor: Defending LLM Agents Against Prompt Injection via Semantic Virtualization

Zonghao Ying, Haozheng Wang, Jiangfan Liu +5

Large Language Model (LLM) agents are increasingly used to automate complex workflows, but integrating untrusted external data with privileged execution exposes them to severe secu…

cs.CR2026

Evolving Deception: When Agents Evolve, Deception Wins

Zonghao Ying, Haowen Dai, Tianyuan Zhang +6

Self-evolving agents offer a promising path toward scalable autonomy. However, in this work, we show that in competitive environments, self-evolution can instead give rise to a ser…

cs.CR2026

Two Frames Matter: A Temporal Attack for Text-to-Video Model Jailbreaking

Moyang Chen, Zonghao Ying, Wenzhuo Xu +4

Recent text-to-video (T2V) models can synthesize complex videos from lightweight natural language prompts, raising urgent concerns about safety alignment in the event of misuse in…

cs.CV2026

DIVER: Dynamic Iterative Visual Evidence Reasoning for Multimodal Fake News Detection

Weilin Zhou, Zonghao Ying, Chunlei Meng +6

Multimodal fake news detection is crucial for mitigating adversarial misinformation. Existing methods, relying on static fusion or LLMs, face computational redundancy and hallucina…

cs.CV2026

SAPL: Semantic-Agnostic Prompt Learning in CLIP for Weakly Supervised Image Manipulation Localization

Xinghao Wang, Changtao Miao, Dianmo Sheng +6

Malicious image manipulation threatens public safety and requires efficient localization methods. Existing approaches depend on costly pixel-level annotations which make training e…