arXiv:2606.13192v1 Announce Type: new Abstract: User experience (UX) centered on usability, perceived consistency, and functional clarity is fundamental to real-world user interfaces (UI). The application of multimodal large language models (MLLMs) in the field of user interfaces is evolving rapidly, such as visual element grounding, graphical user interface (GUI) agents, and design-to-code generation. However, research efforts on evaluating UX based on UI screenshots are still immature. To address this, we propose UXBench, a novel multimodal benchmark consisting of 2,000 VQA data samples desi
The rapid advancement of MLLMs and their increasing application in UI/UX necessitates robust evaluation methods to ensure practical utility and user-centric design.
This development addresses a critical gap in evaluating AI's ability to understand and improve human-computer interaction, laying groundwork for more intuitive and effective AI-driven interfaces.
The introduction of UXBench provides a standardized benchmark for assessing MLLMs' reasoning capabilities for user experience, accelerating research and development in this domain.
- · AI developers
- · UX researchers
- · Software companies
- · End-users
- · Companies with poor UI/UX design
- · Manual UX testing services
Improved multimodal LLMs dedicated to UI/UX analysis and generation will emerge.
The cost and time required for UI/UX design and testing will significantly decrease, leading to faster product iterations.
AI could autonomously design and refine entire user interfaces based on inferred user needs and preferences, leading to highly personalized digital experiences.
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Read at arXiv cs.AI