MobileExplorer: Accelerating On-Device Inference for Mobile GUI Agents via Online Exploration
arXiv:2605.26546v1 Announce Type: new Abstract: Mobile graphical user interface (GUI) agents enable AI models to autonomously operate smartphones on behalf of users. However, most existing systems focus primarily on optimizing task accuracy and rely on cloud-hosted models for inference, which introduces privacy concerns and network-dependent latency. As a result, fully on-device deployment of mobile GUI agents remains underexplored. We propose MobileExplorer, a new framework that accelerates on-device inference for vision-based mobile GUI agents via online exploration. The key idea is to explo
The increasing focus on AI agents' practical application and user privacy, combined with advancements in on-device AI capabilities, makes optimizing local inference crucial.
This development moves AI agents closer to widespread, secure, and efficient deployment on personal devices, reducing reliance on cloud infrastructure and enhancing user privacy.
The feasibility of deploying sophisticated AI models locally on mobile devices for GUI automation improves significantly, enabling new agentic applications without constant network connectivity.
- · mobile device manufacturers
- · on-device AI developers
- · privacy-conscious users
- · edge computing providers
- · cloud-dependent AI agent providers
- · data centers focused solely on inference
Wider adoption and development of fully autonomous mobile AI agents become more practical.
Reduced network bandwidth demand for AI agent operations, potentially impacting telecommunications infrastructure needs.
Enhanced personal data security and sovereignty for individual users as more AI processing occurs locally.
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Read at arXiv cs.AI