Yunna Lv — accepted AI-conference papers

2026

PlugGuard: A Streaming Safeguard for Large Models via Latent Dynamics-Guided Risk Detection

Xiaodan Li, Mengjie Wu, Yao Zhu, Yunna Lv, YueFeng Chen, Cen Chen +2

ICML 2026poster

Large models (LMs) are powerful content generators, yet their open‑ended nature can also introduce potential risks, such as generating harmful or biased content. Existing guardrails mostly perform post-hoc detection that may expose unsafe content before it is caught, and the latency constraints furt…

Cited by 0 Source ↗Scholar ↗

2024

Once and for All: Universal Transferable Adversarial Perturbation against Deep Hashing-Based Facial Image Retrieval

Long Tang, Dengpan Ye, Yunna Lv, Chuanxi Chen, Yunming Zhang

AAAI 2024technical

Deep Hashing (DH)-based image retrieval has been widely applied to face-matching systems due to its accuracy and efficiency. However, this convenience comes with an increased risk of privacy leakage. DH models inherit the vulnerability to adversarial attacks, which can be used to prevent the retriev…

Cited by 9 Source ↗PDF ↗Scholar ↗