UXBench: Measuring the Actionability of LLM-Generated UX Critiques
UXBench evaluates how reliable and useful large language models are when acting as judges for user interfaces. The benchmark tests if LLM critiques lead to actual, measurable improvements in the interface when fixed repair agents apply those changes. Results show models vary significantly in the quality and type of actionable feedback they generate.