Papers by Yinheng Li

2 papers
Do GUI Grounders Truly Understand UI Elements? (2026.findings-eacl)

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Challenge: Existing grounding models and benchmarks are skewed toward web and mobile environments, neglecting desktop interfaces (especially windows).
Approach: They propose a GUI Grounding Sensitivity Benchmark to assess UI grounding sensitivity to multiple descriptions of the same UI element.
Outcome: The proposed model generates multiple valid instructions per UI element and develops nuanced validation methods to validate them.
WinSpot: GUI Grounding Benchmark with Multimodal Large Language Models (2025.acl-short)

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Challenge: Existing GUI grounding data focuses on web-based elements, leaving a gap in real-world GUI interaction data for non-web applications.
Approach: They propose a framework that leverages Large Language Models to generate large-scale GUI grounding data.
Outcome: The framework validates and refines 5,000 GUI coordinate-instruction pairs and provides high-quality data for training and evaluating visual GUI agents.

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