activity
20232026
most citedROS-LLM: A ROS framework for embodied AI with task feedback and structured reasoning

3 citations · 15 across the 24 of their papers we have counts for

collaborators
Showing 2025 · cs.AIShow all

6 papers · 2 filters

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

Adapting Like Humans: A Metacognitive Agent with Test-time Reasoning

Yang Li, Zhiyuan He, Yuxuan Huang +5

Recent Vision-Language Models (VLMs) exhibit strong perceptual reasoning abilities, yet they often struggle to adapt efficiently when encountering novel tasks at test time. In cont…

cs.AI2025

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★ 2 cited

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

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.AI2025

AppVLM: A Lightweight Vision Language Model for Online App Control

Georgios Papoudakis, Thomas Coste, Zhihao Wu +3

The utilisation of foundation models as smartphone assistants, termed app agents, is a critical research challenge. These agents aim to execute human instructions on smartphones by…