13 papers
From Inaudible Inputs to Model Failures: Low-Frequency Safety Risks in LALMs
Yuanhe Zhang, Weiliu Wang, Jie Ren +7
Large audio-language models (LALMs) have demonstrated strong capabilities in understanding diverse audio inputs. This diversity includes low-frequency signals that are inaudible to…
A Unified Framework for the Evaluation of LLM Agentic Capabilities
Pengyu Zhu, Lijun Li, Yaxing Lyu +8
As LLMs are increasingly deployed as agents, reliable assessment of their agentic capabilities has become essential. However, reported benchmark scores often jointly reflect model…
Structure-Guided Visual Perturbation Neutralization for LVLMs
Yuanhe Zhang, Xueting Wang, YanBin Ren +6
Image inputs enable Large Vision Language Models (LVLMs) to perceive fine-grained visual information, but also introduce a pixel-level attack surface through which adversarial pert…
"LLM Agent Performance" Is Not a Single Evaluation Target
Pengyu Zhu, Li Sun, Philip S. Yu +1
LLM agent benchmark scores are shaped not only by the model but also by the agent harness, environment, evaluator, and inference budget. Unified execution controls these non-model…
Resource Consumption Threats in Large Language Models
Yuanhe Zhang, Xinyue Wang, Zhican Chen +8
Given limited and costly computational infrastructure, resource efficiency is a key requirement for large language models (LLMs). Efficient LLMs increase service capacity for provi…
From Helpfulness to Toxic Proactivity: Diagnosing Behavioral Misalignment in LLM Agents
Xinyue Wang, Yuanhe Zhang, Zhengshuo Gong +6
The enhanced capabilities of LLM-based agents come with an emergency for model planning and tool-use abilities. Attributing to helpful-harmless trade-off from LLM alignment, agents…