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20242026
most citedDeep Research Agents: A Systematic Examination And Roadmap

2 citations · 4 across the 13 of their papers we have counts for

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10 papers · 1 filter

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

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.LG2025

Succeed or Learn Slowly: Sample Efficient Off-Policy Reinforcement Learning for Mobile App Control

Georgios Papoudakis, Thomas Coste, Jianye Hao +2

Reinforcement learning (RL) using foundation models for policy approximations in multi-turn tasks remains challenging. We identify two main limitations related to sparse reward set…

cs.CV2025

Uncertainty-quantified Rollout Policy Adaptation for Unlabelled Cross-domain Temporal Grounding

Jian Hu, Zixu Cheng, Shaogang Gong +4

Video Temporal Grounding (TG) aims to temporally locate video segments matching a natural language description (a query) in a long video. While Vision-Language Models (VLMs) are ef…

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.HC2025

ViMo: A Generative Visual GUI World Model for App Agents

Dezhao Luo, Bohan Tang, Kang Li +6

App agents, which autonomously operate mobile Apps through Graphical User Interfaces (GUIs), have gained significant interest in real-world applications. Yet, they often struggle w…

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…

cs.LG2025

Generative Models in Decision Making: A Survey

Xinyu Shao, Jianping Zhang, Haozhi Wang +9

Generative models have fundamentally reshaped the landscape of decision-making, reframing the problem from pure scalar reward maximization to high-fidelity trajectory generation an…

cs.LG2025★ 1 cited

Advancing Autonomous VLM Agents via Variational Subgoal-Conditioned Reinforcement Learning

Qingyuan Wu, Jianheng Liu, Jianye Hao +2

State-of-the-art (SOTA) reinforcement learning (RL) methods have enabled vision-language model (VLM) agents to learn from interaction with online environments without human supervi…