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Plover system externalizes GUI agent plans for improved control and transparency

By PulseAugur Editorial · [2 sources] ·

Researchers have developed Plover, a novel system designed to improve the transparency and controllability of graphical user interface (GUI) automation agents. Unlike previous agents that keep their planning processes internal, Plover externalizes task plans, making them inspectable and editable by users. This plan-centric approach allows for explicit supervision, localized corrections, and natural language guidance, enhancing the adaptability and reliability of GUI automation in dynamic environments. A study involving six participants informed the design, and subsequent evaluations demonstrated Plover's effectiveness in repairing agent failures and improving workflow analyses. AI

IMPACT Enhances transparency and control in GUI automation, potentially improving user interaction with AI agents.

RANK_REASON The cluster contains a research paper detailing a new system for GUI automation.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Plover system externalizes GUI agent plans for improved control and transparency

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The cluster contains a research paper detailing a new system for GUI automation.
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Madhumitha Venkatesan, Shicheng Wen, Jiajing Guo, Jorge Piazentin Ono, Liu Ren, Dongyu Liu ·

    Plover: Steering GUI Agents through Plan-Centric Interaction

    arXiv:2607.15193v1 Announce Type: new Abstract: Graphical user interface (GUI) automation remains challenging in real-world environments, where dynamic layouts, unexpected dialogs, and evolving interface states can cause autonomous agents to drift from user intent. Recent vision-…

  2. arXiv cs.AI TIER_1 English(EN) · Dongyu Liu ·

    Plover: Steering GUI Agents through Plan-Centric Interaction

    Graphical user interface (GUI) automation remains challenging in real-world environments, where dynamic layouts, unexpected dialogs, and evolving interface states can cause autonomous agents to drift from user intent. Recent vision-based multimodal agents improve flexibility by o…

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