From the 1 of 18 linked papers with an AI index.
18 papers
On Success and Simplicity: A Second Look at Transferable Vision-Language Attack Pipeline
Yuchen Ren, Zhengyu Zhao, Chenhao Lin +2
The paper introduces SimVLA, a simplified vision‑language adversarial attack pipeline that improves transferability and computational efficiency compared to existing complex method…
Pay Less Attention to Function Words for Free Robustness of Vision-Language Models
Qiwei Tian, Chenhao Lin, Zhengyu Zhao +1
To address the trade-off between robustness and performance for robust VLM, we observe that function words could incur vulnerability of VLMs against cross-modal adversarial attacks…
Adversarial Video Promotion Against Text-to-Video Retrieval
Qiwei Tian, Chenhao Lin, Zhengyu Zhao +3
Thanks to the development of cross-modal models, text-to-video retrieval (T2VR) is advancing rapidly, but its robustness remains largely unexamined. Existing attacks against T2VR a…
Privacy on the Fly: A Predictive Adversarial Transformation Network for Mobile Sensor Data
Tianle Song, Chenhao Lin, Yang Cao +5
Mobile motion sensors such as accelerometers and gyroscopes are now ubiquitously accessible by third-party apps via standard APIs. While enabling rich functionalities like activity…
Use as Many Surrogates as You Want: Selective Ensemble Attack to Unleash Transferability without Sacrificing Resource Efficiency
Bo Yang, Hengwei Zhang, Jindong Wang +4
In surrogate ensemble attacks, using more surrogate models yields higher transferability but lower resource efficiency. This practical trade-off between transferability and efficie…
A Survey of Defenses Against AI-Generated Visual Media: Detection,Disruption, and Authentication
Jingyi Deng, Chenhao Lin, Zhengyu Zhao +4
Deep generative models have demonstrated impressive performance in various computer vision applications, including image synthesis, video generation, and medical analysis. Despite…