TransBench: Breaking Barriers for Transferable Graphical User Interface Agents in Dynamic Digital Environments
This addresses the challenge of making GUI agents more transferable for real-world automation and accessibility, though it is incremental as it focuses on benchmarking rather than a new agent method.
The paper tackles the problem of GUI agents struggling to adapt to dynamic digital environments by introducing TransBench, a benchmark for evaluating transferability across versions, platforms, and applications, resulting in significant improvements in grounding accuracy.
Graphical User Interface (GUI) agents, which autonomously operate on digital interfaces through natural language instructions, hold transformative potential for accessibility, automation, and user experience. A critical aspect of their functionality is grounding - the ability to map linguistic intents to visual and structural interface elements. However, existing GUI agents often struggle to adapt to the dynamic and interconnected nature of real-world digital environments, where tasks frequently span multiple platforms and applications while also being impacted by version updates. To address this, we introduce TransBench, the first benchmark designed to systematically evaluate and enhance the transferability of GUI agents across three key dimensions: cross-version transferability (adapting to version updates), cross-platform transferability (generalizing across platforms like iOS, Android, and Web), and cross-application transferability (handling tasks spanning functionally distinct apps). TransBench includes 15 app categories with diverse functionalities, capturing essential pages across versions and platforms to enable robust evaluation. Our experiments demonstrate significant improvements in grounding accuracy, showcasing the practical utility of GUI agents in dynamic, real-world environments. Our code and data will be publicly available at GitHub.