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Falcon-ui: Understanding gui before following user instructions

3 Pith papers cite this work. Polarity classification is still indexing.

3 Pith papers citing it

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citation-polarity summary

fields

cs.AI 3

years

2026 3

verdicts

UNVERDICTED 3

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representative citing papers

DRS-GUI: Dynamic Region Search for Training-Free GUI Grounding

cs.AI · 2026-05-15 · unverdicted · novelty 5.0

DRS-GUI introduces a dynamic region search method with Focus/Shift/Scatter actions and MCTS-based planning that improves GUI grounding accuracy by 14% on ScreenSpot-Pro for both general and GUI-specific MLLMs without any training.

GUI Agents with Reinforcement Learning: Toward Digital Inhabitants

cs.AI · 2026-04-30 · unverdicted · novelty 5.0

The paper delivers the first comprehensive overview of RL for GUI agents, organizing methods into offline, online, and hybrid strategies while analyzing trends in rewards, efficiency, and deliberation to outline a future roadmap.

How Mobile World Model Guides GUI Agents?

cs.AI · 2026-05-11 · unverdicted · novelty 4.0 · 2 refs

World models trained on delta text, full text, diffusion images, and renderable code achieve SoTA on two benchmarks and improve downstream GUI agent performance on three mobile datasets with modality-specific strengths.

citing papers explorer

Showing 3 of 3 citing papers.

  • DRS-GUI: Dynamic Region Search for Training-Free GUI Grounding cs.AI · 2026-05-15 · unverdicted · none · ref 28

    DRS-GUI introduces a dynamic region search method with Focus/Shift/Scatter actions and MCTS-based planning that improves GUI grounding accuracy by 14% on ScreenSpot-Pro for both general and GUI-specific MLLMs without any training.

  • GUI Agents with Reinforcement Learning: Toward Digital Inhabitants cs.AI · 2026-04-30 · unverdicted · none · ref 61

    The paper delivers the first comprehensive overview of RL for GUI agents, organizing methods into offline, online, and hybrid strategies while analyzing trends in rewards, efficiency, and deliberation to outline a future roadmap.

  • How Mobile World Model Guides GUI Agents? cs.AI · 2026-05-11 · unverdicted · none · ref 29 · 2 links

    World models trained on delta text, full text, diffusion images, and renderable code achieve SoTA on two benchmarks and improve downstream GUI agent performance on three mobile datasets with modality-specific strengths.