activity
20242026
most citedR-Judge: Benchmarking Safety Risk Awareness for LLM Agents

2 citations · 3 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2026

Faithful Mobile GUI Agents with Guided Advantage Estimator

Haowen Hu, Pengzhou Cheng, Zheng Wu +3

Vision-language model based graphical user interface (GUI) agents have shown strong interaction capabilities. However, they often behave unfaithfully, relying on memorized shortcut…

cs.CL2026

OS-SPEAR: A Toolkit for the Safety, Performance,Efficiency, and Robustness Analysis of OS Agents

Zheng Wu, Yi Hua, Zhaoyuan Huang +8

The evolution of Multimodal Large Language Models (MLLMs) has shifted the focus from text generation to active behavioral execution, particularly via OS agents navigating complex G…

cs.CV2026

Zooming without Zooming: Region-to-Image Distillation for Fine-Grained Multimodal Perception

Lai Wei, Liangbo He, Jun Lan +9

Multimodal Large Language Models (MLLMs) excel at broad visual understanding but still struggle with fine-grained perception, where decisive evidence is small and easily overwhelme…

cs.CL2025

Agent-ScanKit: Unraveling Memory and Reasoning of Multimodal Agents via Sensitivity Perturbations

Pengzhou Cheng, Lingzhong Dong, Zeng Wu +5

Although numerous strategies have recently been proposed to enhance the autonomous interaction capabilities of multimodal agents in graphical user interface (GUI), their reliabilit…

cs.CL2025

Say One Thing, Do Another? Diagnosing Reasoning-Execution Gaps in VLM-Powered Mobile-Use Agents

Lingzhong Dong, Ziqi Zhou, Shuaibo Yang +6

Mobile-use agents powered by vision-language models (VLMs) have shown great potential in interpreting natural language instructions and generating corresponding actions based on mo…

cs.AI2025★ 1 cited

See, Think, Act: Teaching Multimodal Agents to Effectively Interact with GUI by Identifying Toggles

Zongru Wu, Rui Mao, Zhiyuan Tian +7

The advent of multimodal agents facilitates effective interaction within graphical user interface (GUI), especially in ubiquitous GUI control. However, their inability to reliably…

cs.LG2025

GEM: Gaussian Embedding Modeling for Out-of-Distribution Detection in GUI Agents

Zheng Wu, Pengzhou Cheng, Zongru Wu +2

Graphical user interface (GUI) agents have recently emerged as an intriguing paradigm for human-computer interaction, capable of automatically executing user instructions to operat…

cs.CL2024★ 2 cited

R-Judge: Benchmarking Safety Risk Awareness for LLM Agents

Tongxin Yuan, Zhiwei He, Lingzhong Dong +9

Large language models (LLMs) have exhibited great potential in autonomously completing tasks across real-world applications. Despite this, these LLM agents introduce unexpected saf…