7 papers
Where World Models Break: Natural-Input Failure Discovery
Zhanpeng Shi, Zi Liang, Rong Feng +3
World models predict action-conditioned futures and serve as critical internal simulators for downstream planning and control. However, catastrophic prediction failures of world mo…
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…
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…
Balancing Efficiency and Fairness: An Iterative Exchange Framework for Multi-UAV Cooperative Path Planning
Hongzong Li, Luwei Liao, Xiangguang Dai +3
Multi-UAV cooperative path planning (MUCPP) is a fundamental problem in multi-agent systems, aiming to generate collision-free trajectories for a team of unmanned aerial vehicles (…
Particle Dynamics for Latent-Variable Energy-Based Models
Shiqin Tang, Shuxin Zhuang, Rong Feng +3
Latent-variable energy-based models (LVEBMs) assign a single normalized energy to joint pairs of observed data and latent variables, offering expressive generative modeling while c…
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…