Towards Scalable Lightweight GUI Agents via Multi-role Orchestration
Autonomous Graphical User Interface (GUI) agents powered by Multimodal Large Language Models (MLLMs) enable digital automation on end-user devices. While scaling both parameters and data has yielded substantial gains, advanced methods still suffer from prohibitive deployment costs on resource-constrained devices. When facing complex in-the-wild scenarios, lightweight GUI agents are bottlenecked by limited capacity and poor task scalability under end-to-end episodic learning, impeding adaptation to multi-agent systems (MAS), while training multiple skill-specific experts remains costly. Can we strike an effective trade-off in this cost-scalability dilemma, enabling lightweight MLLMs to par...
| Authors | Ziwei Wang, Junjie Zheng, Leyang Yang et al. |
|---|---|
| Primary category | cs.AI |
| Published | 15 April 2026 |
| Last updated at source | 15 April 2026 |
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