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

Project Page arXiv HuggingFace Models Datasets Benchmark Results License

MobileForge turns real target-app interaction into executable curricula, hierarchical rollout feedback, and hint-contextualized policy updates without human-written tasks, demonstrations, or reward labels.

🔥 News

📊 Main Results

MobileForge main benchmark performance

MobileForge improves mobile GUI agents through annotation-free target-app adaptation. With GUI-Owl-1.5-8B, MobileForge reaches 67.24% Pass@1 and 77.59% Pass@3 on AndroidWorld, and 41.03% SR on MobileWorld. With Qwen3-VL-8B, MobileForge raises AndroidWorld Pass@3 to 67.24%.

🧩 Overview

MobileForge adapts mobile GUI agents without collecting task-specific human annotations. It combines MobileGym for target-app exploration and automatic curriculum generation with HiFPO for hint-guided rollout, hierarchical trajectory feedback, and step-level GRPO training.

MobileGym: target-app interaction and hierarchical feedback

MobileGym grounds the adaptation loop in real target-app interaction. It explores Android apps, mines executable curriculum tasks from interaction traces, executes rollouts, and evaluates completed attempts with outcome labels, step-level process feedback, and corrective hints.

MobileGym framework

HiFPO: feedback-guided policy optimization

HiFPO turns MobileGym feedback into training signals. It runs hint-guided multi-attempt rollouts, filters mastered tasks and low-quality steps, retains informative experience, and trains the agent with hint-contextualized step-level GRPO.

HiFPO optimization pipeline

📁 Repository Guide

MobileForge/
|-- explore/                       # Target-app exploration and MobileGym-Curriculum task generation
|-- rollout/                       # Hint-guided rollout, critic feedback, and rollout-to-GRPO processing
|-- training/                      # VERL-derived MobileForge step-level GRPO training stack
|-- evaluation/
|   |-- androidworld/              # AndroidWorld evaluation fork and reproduction utilities
|   `-- mobileworld/               # MobileWorld reproduction notes and helpers
|-- docs/                          # Models, data release, pipeline, and evaluation-result mapping
|-- metadata/                      # Public release manifests and model/result maps
|-- CITATION.cff
|-- citations.bib
`-- README.md

🚀 Where to Start

The root README is intentionally concise. Detailed setup and commands live in the component README files.

Goal Start here What it covers
Explore target apps and generate tasks explore/ Target-app exploration, APK cache, parallel exploration, and MobileGym-Curriculum task generation.
Run hint-guided rollouts and build GRPO data rollout/ Multi-attempt rollout, MobileGym-Critic feedback, hint reuse, and rollout-to-training-data conversion.
Train with HiFPO / step-level GRPO training/ Training environment, GRPO launch script, reward function, and utility tools.
Reproduce benchmark runs evaluation/ and docs/evaluation_results.md AndroidWorld and MobileWorld artifact mapping and evaluation notes.
Inspect release manifests docs/ and metadata/ Model list, dataset release notes, pipeline overview, and model-to-result mapping.

📦 Release Index

Artifact Link Details
Models 🤗 MobileForge Models collection Main ForgeQwen3 / ForgeOwl checkpoints and scaling-ablation checkpoints. See docs/models.md.
Datasets 🤗 MobileForge Datasets collection Training data, exploration trajectories, and generated tasks. See docs/data_release.md.
Benchmark results 🤗 lgy0404/mobileforge-benchmark-results AndroidWorld and MobileWorld archives. See docs/evaluation_results.md.
Paper arXiv:2606.19930 Technical report and citation metadata.

Citation

@article{liu2026mobileforge,
  title={MobileForge: Annotation-Free Adaptation for Mobile GUI Agents with Hierarchical Feedback-Guided Policy Optimization},
  author={Liu, Guangyi and Zhao, Pengxiang and Wu, Gao and Yin, Yiwen and Li, Mading and Liu, Liang and Liu, Congxiao and Qi, Zhang and Wang, Mengyan and Guo, Liang and others},
  journal={arXiv preprint arXiv:2606.19930},
  year={2026}
}

Contact

For questions about the paper, code, or released artifacts, contact guangyiliu@zju.edu.cn.

⭐ Star History

Star History Chart

🙏 Acknowledgements

MobileForge builds on open-source resources including AndroidWorld, MobileWorld, MobileAgent, Qwen3-VL, GUI-explorer, VERL, and GUI-R1.

About

Official code repo for the paper "MobileForge: Annotation-Free Adaptation for Mobile GUI Agents with Hierarchical Feedback-Guided Policy Optimization"

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