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

1 citations · 1 across the 13 of their papers we have counts for

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6 papers · 1 filter

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…

cs.LG2025

GUI-G: Gaussian Reward Modeling for GUI Grounding

Fei Tang, Zhangxuan Gu, Zhengxi Lu +9

Graphical User Interface (GUI) grounding maps natural language instructions to precise interface locations for autonomous interaction. Current reinforcement learning approaches use…

cs.CV2025

SVGenius: Benchmarking LLMs in SVG Understanding, Editing and Generation

Siqi Chen, Xinyu Dong, Haolei Xu +10

Large Language Models (LLMs) and Multimodal LLMs have shown promising capabilities for SVG processing, yet existing benchmarks suffer from limited real-world coverage, lack of comp…

cs.HC2025★ 1 cited

A Survey on (M)LLM-Based GUI Agents

Fei Tang, Haolei Xu, Hang Zhang +12

Graphical User Interface (GUI) Agents have emerged as a transformative paradigm in human-computer interaction, evolving from rule-based automation scripts to sophisticated AI-drive…

cs.AI2025

Think Twice, Click Once: Enhancing GUI Grounding via Fast and Slow Systems

Fei Tang, Yongliang Shen, Hang Zhang +7

Humans can flexibly switch between different modes of thinking based on task complexity: from rapid intuitive judgments to in-depth analytical understanding. However, current Graph…