most citedSkillJect: Effectively Automating Skill-Based Prompt Injection for Skill-Enabled Agents

1 citations · 1 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CR20261 cited

SkillJect: Effectively Automating Skill-Based Prompt Injection for Skill-Enabled Agents

Xiaojun Jia, Jie Liao, Simeng Qin +5

Agent skills extend LLM agents with task-specific instructions, executable scripts, and auxiliary resources, improving reusability but creating a new supply-chain attack surface. A…

cs.AI2026

The Latent Space: Foundation, Evolution, Mechanism, Ability, and Outlook

Xinlei Yu, Zhangquan Chen, Yongbo He +36

Latent space is rapidly emerging as a native substrate for language-based models. While modern systems are still commonly understood through explicit token-level generation, an inc…

cs.AI2026

ODAR: Principled Adaptive Routing for LLM Reasoning via Active Inference

Siyuan Ma, Bo Gao, Xiaojun Jia +6

The paradigm of large language model (LLM) reasoning is shifting from parameter scaling to test-time compute scaling, yet many existing approaches still rely on uniform brute-force…

cs.LG2026

M3-AD: Reflection-aware Multi-modal, Multi-category, and Multi-dimensional Benchmark and Framework for Industrial Anomaly Detection

Chao Huang, Yanhui Li, Yunkang Cao +5

Although multimodal large language models (MLLMs) have advanced industrial anomaly detection toward a zero-shot paradigm, they still tend to produce high-confidence yet unreliable…

cs.CR2025

OmniSafeBench-MM: A Unified Benchmark and Toolbox for Multimodal Jailbreak Attack-Defense Evaluation

Xiaojun Jia, Jie Liao, Qi Guo +11

Recent advances in multi-modal large language models (MLLMs) have enabled unified perception-reasoning capabilities, yet these systems remain highly vulnerable to jailbreak attacks…

cs.CR2025

Heuristic-Induced Multimodal Risk Distribution Jailbreak Attack for Multimodal Large Language Models

Ma Teng, Jia Xiaojun, Duan Ranjie +5

With the rapid advancement of multimodal large language models (MLLMs), concerns regarding their security have increasingly captured the attention of both academia and industry. Al…