7 papers
Adversarial Attacks on Deep OCR Systems
Wenbo Sun, Hongzong LI, Yanyun Wang +5
Deep-OCR (DeepSeek-OCR) advances document recognition by treating the visual modality as an optical compression medium, enabling long-context OCR at low token cost. However, its in…
GraphChase: A Platform and Benchmark for Urban Network Security Games
Shuxin Zhuang, Shuxin Li, Tianji Yang +4
After the achievement of solving two-player zero-sum games, more AI researchers focus on solving multiplayer games. Urban Network Security Games (\textbf{UNSGs}) represent a class…
Adversary-Free Counterfactual Prediction via Information-Regularized Representations
Shiqin Tang, Rong Feng, Shuxin Zhuang +2
We study counterfactual prediction under assignment bias and propose a mathematically grounded, information-theoretic approach that removes treatment-covariate dependence without a…
How Vulnerable Are Edge LLMs?
Ao Ding, Hongzong Li, Zi Liang +5
Large language models (LLMs) are increasingly deployed on edge devices under strict computation and quantization constraints, yet their security implications remain unclear. We stu…
How Much Information Can a Vision Token Hold? A Scaling Law for Recognition Limits in VLMs
Shuxin Zhuang, Zi Liang, Runsheng Yu +4
Recent vision-centric approaches have made significant strides in long-context modeling. Represented by DeepSeek-OCR, these models encode rendered text into continuous vision token…
Tree-Based Stochastic Optimization for Solving Large-Scale Urban Network Security Games
Shuxin Zhuang, Linjian Meng, Shuxin Li +2
Urban Network Security Games (UNSGs), which model the strategic allocation of limited security resources on city road networks, are critical for urban safety. However, finding a Na…