3 papers
cs.CV2026
RobustVLA: On Robustness of Vision-Language-Action Model against Multi-Modal Perturbations
Jianing Guo, Zhenhong Wu, Chang Tu +13
In Vision-Language-Actionf(VLA) models, robustness to real-world perturbations is critical for deployment. Existing methods target simple visual disturbances, overlooking the broad…
cs.HC2025
The Pervasive Blind Spot: Benchmarking VLM Inference Risks on Everyday Personal Videos
Shuning Zhang, Zhaoxin Li, Changxi Wen +8
The proliferation of Vision-Language Models (VLMs) introduces profound privacy risks from personal videos. This paper addresses the critical yet unexplored inferential privacy thre…
cs.DB2025
PBE Meets LLM: When Few Examples Aren't Few-Shot Enough
Shuning Zhang, Yongjoo Park
Large language models (LLMs) can generate code from natural language descriptions. Their performance is typically evaluated using programming benchmarks that simulate real-world ta…