UI-R1 framework enhances multimodal large language models to better predict user actions in graphical interfaces by applying reinforcement learning with rule-based rewards.

• Achieves state-of-the-art performance on WebShop benchmark with a 17.8% improvement
• Demonstrates 19.8% higher success rate on complex multi-step UI operations
• Creates more robust agents that provide better reasoning explanations for their actions
• Significantly improves performance with just 2,000 training examples

This engineering breakthrough enables more reliable GUI automation tools, more intuitive digital assistants, and improved accessibility features across applications.

UI-R1: Enhancing Action Prediction of GUI Agents by Reinforcement Learning