collaborators
Showing cs.AIShow all

8 papers · 1 filter

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

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

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…

cs.AI2025

Deep Research Agents: A Systematic Examination And Roadmap

Yuxuan Huang, Yihang Chen, Haozheng Zhang +10

The rapid progress of Large Language Models (LLMs) has given rise to a new category of autonomous AI systems, referred to as Deep Research (DR) agents. These agents are designed to…

cs.AI2025

SPA-Bench: A Comprehensive Benchmark for SmartPhone Agent Evaluation

Jingxuan Chen, Derek Yuen, Bin Xie +14

Smartphone agents are increasingly important for helping users control devices efficiently, with (Multimodal) Large Language Model (MLLM)-based approaches emerging as key contender…