10 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…
Controlled Memory Interference in Continual LLM Agents
Ao Ding, Hongzong LI, Shiqin Tang +4
Long-term memory enables AI agents to maintain continuity across sessions, personalize behavior, and evolve through accumulated experience. Yet memory evolution is not simply a pro…
EMAN: Optimization-Driven Capacity Growth through Path Emergence in Multi-Task Learning
Chenlei Fang, Jingchen Li, Hongzong LI +5
Existing multi-task learning methods rely on hard sharing, multiple paths or experts, adaptive sharing, and dynamic expansion. However, their capacity changes are usually constrain…
Efficient Online Lexicographic Generalized Low-Rank Matrix Bandits
Bo Xue, Ji Cheng, Haodong Jing +2
This paper studies generalized low-rank matrix bandits with multiple prioritized objectives. At each round, the learner selects a matrix-valued arm and observes a vector-valued rew…
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…