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cs.AI2026

Darwin Mobile Agent: A Roadmap for Self-Evolution

Daniel Beechey, Derek Yuen, Jianheng Liu +5

The goal of artificial intelligence is to create agents capable of general, adaptive behaviour in open-ended environments. Guided by the "Bitter Lesson", we argue that the most eff…

cs.AI2026

EE-MCP: Self-Evolving MCP-GUI Agents via Automated Environment Generation and Experience Learning

Tiantian He, Yihang Chen, Keyue Jiang +4

Computer-use agents that combine GUI interaction with structured API calls via the Model Context Protocol (MCP) show promise for automating software tasks. However, existing approa…

cs.AI2026

Beyond Syntax: Action Semantics Learning for App Agents

Bohan Tang, Dezhao Luo, Jianheng Liu +5

The recent development of Large Language Models (LLMs) enables the rise of App agents that interpret user intent and operate smartphone Apps through actions such as clicking and sc…

cs.AI2026

InfoSeeker: A Scalable Hierarchical Parallel Agent Framework for Web Information Seeking

Ka Yiu Lee, Yuxuan Huang, Zhiyuan He +5

Recent agentic search systems have made substantial progress by emphasising deep, multi-step reasoning. However, this focus often overlooks the challenges of wide-scale information…

cs.AI2026

Hi-Agent: Hierarchical Vision-Language Agents for Mobile Device Control

Zhe Wu, Hongjin Lu, Junliang Xing +10

Building agents that autonomously operate mobile devices has attracted increasing attention. While Vision-Language Models (VLMs) show promise, most existing approaches rely on dire…

cs.AI2025

See-Control: A Multimodal Agent Framework for Smartphone Interaction with a Robotic Arm

Haoyu Zhao, Weizhong Ding, Yuhao Yang +4

Recent advances in Multimodal Large Language Models (MLLMs) have enabled their use as intelligent agents for smartphone operation. However, existing methods depend on the Android D…