UI-MOPD: Multi-Platform On-Policy Distillation for Continual GUI Agent Learning
- Published
- Source
- arXiv
- Paper number
- 568
- Field
- LLMs / NLP
- arXiv ID
- 2607.04425
Key points
- MOPD, multi-teacher on-policy distillation, is introduced for the first time to continual cross-platform learning for GUI agents.
- Uni-GUI is a dataset of about 10K high-quality cross-platform GUI interaction trajectories.
- A platform router dynamically selects a teacher based on the environment, mixing behavior rules and preventing catastrophic forgetting.
- It achieves relative gains of 38.2% on OSWorld and 12.0% on MobileWorld, or 12.7% and 55.8% depending on the baseline, showing that a single 8B model improves on both platforms at once.
- GUI grounding ability is also preserved, with 43.14% on ScreenSpot-Pro and 90.88% on ScreenSpotV2, showing minimal loss relative to the base model.
Paper links
External research summaries. These are not HDATF publications or measured product results.