activity
20242026
most citedA Survey on (M)LLM-Based GUI Agents

1 citations · 1 across the 8 of their papers we have counts for

collaborators

11 papers

cs.CV2026

UI-Zoomer: Uncertainty-Driven Adaptive Zoom-In for GUI Grounding

Fei Tang, Bofan Chen, Zhengxi Lu +8

GUI grounding, which localizes interface elements from screenshots given natural language queries, remains challenging for small icons and dense layouts. Test-time zoom-in methods…

cs.LG2026

UI-Copilot: Advancing Long-Horizon GUI Automation via Tool-Integrated Policy Optimization

Zhengxi Lu, Fei Tang, Guangyi Liu +8

MLLM-based GUI agents have demonstrated strong capabilities in complex user interface interaction tasks. However, long-horizon scenarios remain challenging, as these agents are bur…

cs.LG2026

ClawGUI: A Unified Framework for Training, Evaluating, and Deploying GUI Agents

Fei Tang, Zhiqiong Lu, Boxuan Zhang +4

GUI agents drive applications through their visual interfaces instead of programmatic APIs, interacting with arbitrary software via taps, swipes, and keystrokes, reaching a long ta…

cs.AI2026

KnowU-Bench: Towards Interactive, Proactive, and Personalized Mobile Agent Evaluation

Tongbo Chen, Zhengxi Lu, Zhan Xu +13

Personalized mobile agents that infer user preferences and calibrate proactive assistance hold great promise as everyday digital assistants, yet existing benchmarks fail to capture…

cs.LG2025

UI-S1: Advancing GUI Automation via Semi-online Reinforcement Learning

Zhengxi Lu, Jiabo Ye, Fei Tang +8

Graphical User Interface (GUI) agents have demonstrated remarkable progress in automating complex user interface interactions through reinforcement learning. However, current appro…

cs.CV2025

Test-Time Reinforcement Learning for GUI Grounding via Region Consistency

Yong Du, Yuchen Yan, Fei Tang +5

Graphical User Interface (GUI) grounding, the task of mapping natural language instructions to precise screen coordinates, is fundamental to autonomous GUI agents. While existing m…