collaborators

6 papers

cs.HC2026

MobileForge: Annotation-Free Adaptation for Mobile GUI Agents with Hierarchical Feedback-Guided Policy Optimization

Guangyi Liu, Pengxiang Zhao, Gao Wu +9

MLLM-based mobile GUI agents have made substantial progress in UI understanding and action execution, but adapting them to real target apps remains costly because mobile apps are n…

cs.HC2026

MemGUI-Agent: An End-to-End Long-Horizon Mobile GUI Agent with Proactive Context Management

Guangyi Liu, Gao Wu, Congxiao Liu +7

MLLM-based mobile GUI agents have made substantial progress on short-horizon tasks, yet remain unreliable on long-horizon tasks that require retaining intermediate facts across man…

cs.MA2026

FedGUI: Benchmarking Federated GUI Agents across Heterogeneous Platforms, Devices, and Operating Systems

Wenhao Wang, Haoting Shi, Mengying Yuan +7

Training GUI agents with traditional centralized methods faces significant cost and scalability challenges. Federated learning (FL) offers a promising solution, yet its potential i…

cs.LG2026

UI-Copilot: Advancing Long-Horizon GUI Automation via Tool-Integrated Policy Optimization

Zhengxi Lu, Fei Tang, Guangyi Liu +8

MLLM-based GUI agents have demonstrated strong capabilities in complex user interface interaction tasks. However, long-horizon scenarios remain challenging, as these agents are bur…

cs.DC2026

MemGUI-Bench: Benchmarking Memory of Mobile GUI Agents in Dynamic Environments

Guangyi Liu, Pengxiang Zhao, Yaozhen Liang +12

Reliable mobile GUI agents must retain and reuse information across actions, applications, and repeated interactions. However, current benchmarks systematically underrepresent thes…

cs.AI2025

MobileA3gent: Training Mobile GUI Agents Using Decentralized Self-Sourced Data from Diverse Users

Wenhao Wang, Mengying Yuan, Zijie Yu +5

The advancement of mobile GUI agents has opened new opportunities for automating tasks on mobile devices. Training these agents requires large-scale high-quality data, which is pro…