works on

From the 1 of 8 linked papers with an AI index.

collaborators

8 papers

cs.CV2026

PersGuard: Preventing Malicious Personalization in Text-to-Image Diffusion Models via Model Backdoors

Xinwei Liu, Xiaojun Jia, Yuan Xun +2

The paper proposes PersGuard, a backdoor-based method that embeds protective triggers into pre‑trained text‑to‑image diffusion models so that unauthorized fine‑tuning on protected…

cs.CV2026

SGHA-Attack: Semantic-Guided Hierarchical Alignment for Transferable Targeted Attacks on Vision-Language Models

Haobo Wang, Weiqi Luo, Xiaojun Jia +1

Large vision-language models (VLMs) are vulnerable to transfer-based adversarial perturbations, enabling attackers to optimize on surrogate models and manipulate black-box VLM outp…

cs.CV2025

GeoShield: Safeguarding Geolocation Privacy from Vision-Language Models via Adversarial Perturbations

Xinwei Liu, Xiaojun Jia, Yuan Xun +2

Vision-Language Models (VLMs) such as GPT-4o now demonstrate a remarkable ability to infer users' locations from public shared images, posing a substantial risk to geoprivacy. Alth…

cs.CV2025

3D Gaussian Splatting Driven Multi-View Robust Physical Adversarial Camouflage Generation

Tianrui Lou, Xiaojun Jia, Siyuan Liang +4

Physical adversarial attack methods expose the vulnerabilities of deep neural networks and pose a significant threat to safety-critical scenarios such as autonomous driving. Camouf…

cs.CL2025

No Query, No Access

Wenqiang Wang, Siyuan Liang, Yangshijie Zhang +3

Textual adversarial attacks mislead NLP models, including Large Language Models (LLMs), by subtly modifying text. While effective, existing attacks often require knowledge of the v…

cs.AI2025

The Emotional Baby Is Truly Deadly: Does your Multimodal Large Reasoning Model Have Emotional Flattery towards Humans?

Yuan Xun, Xiaojun Jia, Xinwei Liu +1

We observe that MLRMs oriented toward human-centric service are highly susceptible to user emotional cues during the deep-thinking stage, often overriding safety protocols or built…