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cs.AI2026

Just Ask: Curious Code Agents Reveal System Prompts in Frontier LLMs

Xiang Zheng, Yutao Wu, Hanxun Huang +5

Autonomous code agents built on large language models are reshaping software and AI development through tool use, long-horizon reasoning, and self-directed interaction. However, th…

cs.AI2026

AgentDoG 1.5: A Lightweight and Scalable Alignment Framework for AI Agent Safety and Security

Dongrui Liu, Yu Li, Zhonghao Yang +47

Modern open-world agents such as OpenClaw exhibit powerful cross-environment execution capabilities yet introduce broad new safety risk sources. Meanwhile, advanced frontier AI mod…

cs.AI2026

When Direct Prediction Fails: Evidence from LLM-Based Misinformation Risk Evaluation

Zonghuan Xu, Xiang Zheng, Yutao Wu +1

LLMs make it increasingly easy to generate deceptive content at scale, creating a need for scalable misinformation risk evaluation based on whether readers find such content credib…

cs.AI2026

Steering the Verifiability of Multimodal AI Hallucinations

Jianhong Pang, Ruoxi Cheng, Ziyi Ye +4

AI applications driven by multimodal large language models (MLLMs) are prone to hallucinations and pose considerable risks to human users. Crucially, such hallucinations are not eq…

cs.AI2026

AgentHazard: A Benchmark for Evaluating Harmful Behavior in Computer-Use Agents

Yunhao Feng, Yifan Ding, Yingshui Tan +6

Computer-use agents extend language models from text generation to persistent action over tools, files, and execution environments. Unlike chat systems, they maintain state across…

cs.AI2026

Attention in Space: Functional Roles of VLM Heads for Spatial Reasoning

Xueqi Ma, Shuo Yang, Yanbei Jiang +6

Despite remarkable advances in large Vision-Language Models (VLMs), spatial reasoning remains a persistent challenge. In this work, we investigate how attention heads within VLMs c…