Learn How to Act from Your Own Interactions: On-Policy Self-Distillation for GUI Agents

arXiv:2609.27307 · cs.AI · Submitted 2026-09-23 · Read on arXiv

cs.AI

Submitted: 2026-09-23

Updated: 2026-09-23

Terminology

• Distillation — 47× in this paper · explained in 2 episodes
• Self-Distillation — 21× in this paper · explained in 7 episodes
• Benchmark — 16× in this paper · explained in 2 episodes
• Grounding — 13× in this paper · explained in 3 episodes
• GRPO — 12× in this paper · explained in 6 episodes
• Reinforcement Learning — 10× in this paper · explained in 4 episodes
• Accuracy — 7× in this paper · explained in 1 episode
• Analyzer — 3× in this paper · explained in 1 episode
• Ablation — 2× in this paper · explained in 1 episode
• Adaptation — 2× in this paper · explained in 1 episode
• Benchmarking — 2× in this paper · explained in 3 episodes
• Credit assignment — 2× in this paper · explained in 3 episodes
• On-policy Self-Distillation (OPSD) — 2× in this paper · explained in 2 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Verification — 2× in this paper · explained in 2 episodes
• Annotation Errors — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• GRPO Objective — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Graphical User Interface — 1× in this paper
• Model Context Protocol — 1× in this paper
• Model Context Protocol (MCP) — 1× in this paper · explained in 8 episodes
• On-Policy Distillation — 1× in this paper · explained in 3 episodes
• Online Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Reasoning Traces — 1× in this paper · explained in 3 episodes
• Sparse Attention — 1× in this paper · explained in 5 episodes
• Two-Stage Framework — 1× in this paper · explained in 2 episodes
• Two-stage training — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes
• Visual Grounding — 1× in this paper · explained in 2 episodes

Sources

• Qwen3-VL Technical Report
• OpenMobile: Building Open Mobile Agents with Task and Trajectory Synthesis
• UI-Venus Technical Report: Building High-performance UI Agents with RFT
• Trust the Right Teacher: Quality-Aware Self-Distillation for GUI Grounding
• MiniMax Sparse Attention
• Efficient Multi-turn RL for GUI Agents via Decoupled Training and Adaptive Data Curation
• The Next Screenshot Knows: Gated Hindsight Distillation for Mobile GUI Agents
• On-Policy Self-Distillation without Any Supervision
• UI-MOPD: Multi-Platform On-Policy Distillation for Unified GUI Agents
• MobileForge: Annotation-Free Adaptation for Mobile GUI Agents with Hierarchical Feedback-Guided Policy Optimization
• ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay
• UI-S1: Advancing GUI Automation via Semi-online Reinforcement Learning
• Self-Distilled Agentic Reinforcement Learning
• GUI-R1 : A Generalist R1-Style Vision-Language Action Model For GUI Agents
• Negative Self-Distillation: Learning to Reason by Avoiding Flaws
• MobileGUI-RL: Advancing Mobile GUI Agent through Reinforcement Learning in Online Environment
• Gemini: A Family of Highly Capable Multimodal Models
• Kimi K3: Open Frontier Intelligence
• LiteGUI: Distilling Compact GUI Agents with Reinforcement Learning
• Mobile-Agent-v3.5: Multi-platform Fundamental GUI Agents

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