AgentLens: Adaptive Visual Modalities for Human-Agent Interaction in Mobile GUI Agents

· Source: cs.MA updates on arXiv.org · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Robotics & Autonomous Systems, Human-Computer Interaction · Depth: Expert, quick

Summary

AgentLens is a novel mobile GUI agent designed to improve human-agent interaction by adaptively employing three visual modalities: Full UI, Partial UI, and GenUI. Submitted on April 22, 2026, this system addresses the limitations of existing mobile agents that force a choice between transparent foreground execution (preventing multitasking) and background execution (lacking visual awareness). Through iterative formative studies, the researchers found that users prefer a hybrid model with just-in-time visual interaction, where the optimal visualization modality varies by task. AgentLens extends standard mobile agents with adaptive communication actions and utilizes Virtual Display to enable background execution with selective visual overlays. A controlled study with 21 participants showed that 85.7% preferred AgentLens, which also achieved a high usability score of 1.94 Overall PSSUQ and an adoption-intent score of 6.43/7.

Key takeaway

For product designers developing mobile GUI agents, AgentLens demonstrates that offering adaptive visual modalities significantly improves user experience and adoption. You should consider implementing a hybrid interaction model that allows for just-in-time visual feedback, dynamically switching between full, partial, or generated UI views based on task context, to balance transparency with multitasking capabilities.

Key insights

Adaptive visual modalities enhance human-agent interaction in mobile GUI agents, balancing transparency and multitasking.

Principles

Method

AgentLens extends mobile agents with adaptive communication actions and uses Virtual Display for background execution with selective visual overlays, offering Full UI, Partial UI, and GenUI modalities.

In practice

Topics

Best for: AI Scientist, Research Scientist, Product Designer

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Editorial summary, takeaway, and curation by AIssential. Original article published by cs.MA updates on arXiv.org.