The Ferret-UI project enhances multimodal large language models (MLLMs) to understand and interact with user interface (UI) screens effectively. Ferret-UI enhances visual features to focus on smaller UI elements and trains on datasets for elementary and advanced UI tasks.

• Divides the screen into sub-images encoding smaller UI details.
• Curates training samples for tasks like icon recognition and widget listing.
• Compiles dataset for advanced description and function inference tasks.
• Performs excellently in comprehension and open-ended instruction execution.

Opinion: Ferret-UI’s focus on mobile UI understanding could pave the way for more intuitive user experiences and the development of assistive technologies for users with disabilities. Its meticulous training process and data augmentation provide promising strides in mobile UI comprehension.