Publications (9)
Vulnerabilities in Video Quality Assessment Models: The Challenge of Adversarial Attacks
Ao-Xiang Zhang, Yu Ran, Weixuan Tang +1
No-Reference Video Quality Assessment (NR-VQA) plays an essential role in improving the viewing experience of end-users. Driven by deep learning, recent NR-VQA models based on Conv…
Non-homogeneous Problems for Nonlinear Schrödinger Equations in a Strip Domain
Yu Ran, Shu-Ming Sun
This paper studies the initial-boundary-value problem (IBVP) of a nonlinear Schrödinger equation posed on a strip domain with non-homogeneous Dirichlet bou…
ERNIE 5.0 Technical Report
Haifeng Wang, Hua Wu, Tian Wu +432
In this report, we introduce ERNIE 5.0, a natively autoregressive foundation model desinged for unified multimodal understanding and generation across text, image, video, and audio…
Secure Video Quality Assessment Resisting Adversarial Attacks
Ao-Xiang Zhang, Yuan-Gen Wang, Yu Ran +3
The exponential surge in video traffic has intensified the imperative for Video Quality Assessment (VQA). Leveraging cutting-edge architectures, current VQA models have achieved hu…
MissClick: Exploiting Digit-Serialized Coordinates to Attack GUI Grounding Models
Yu Ran, Wentao Zhao, Xin Zhang +1
Recent GUI visual grounding models generate screen coordinates as sequences of digit tokens that are parsed into numerical values and mapped to executable clicks. The security impl…
Black-box Adversarial Attacks Against Image Quality Assessment Models
Yu Ran, Ao-Xiang Zhang, Mingjie Li +2
The goal of No-Reference Image Quality Assessment (NR-IQA) is to predict the perceptual quality of an image in line with its subjective evaluation. To put the NR-IQA models into pr…