New LAMO framework enables lightweight AI models to automate complex GUI tasks on resource-constrained devices through multi-role orchestration

Researchers propose LAMO framework to solve the cost-scalability dilemma in deploying GUI agents on end-user devices with limited computational resources

Lightweight multimodal large language models (MLLMs) can now handle complex real-world GUI automation scenarios without prohibitive deployment costs

Multi-role orchestration approach allows smaller AI models to expand their capabilities for GUI workflows while avoiding expensive training of multiple skill-specific experts

Framework addresses key bottlenecks of lightweight agents including limited capacity and poor task scalability in multi-agent systems (MAS)