The field of mobile agents is rapidly evolving, with a focus on improving accuracy, efficiency, and generalization across tasks, modalities, apps, and devices. Recent developments have led to the creation of more sophisticated mobile agent systems, incorporating multimodal foundation models, retrieval-augmented generation, and cloud-device collaboration. These advancements have enabled mobile agents to better understand user queries, interact with external environments, and learn from previous mistakes. Notable papers in this area include MobiAgent, which achieves state-of-the-art performance in real-world mobile scenarios, and AppCopilot, which operationalizes a full-stack, closed-loop system for mobile agents. Other noteworthy papers are KG-RAG, which enhances GUI agent decision-making via knowledge graph-driven retrieval-augmented generation, and VehicleWorld, which introduces a comprehensive environment for intelligent vehicle interaction.