WinSpot: GUI Grounding Benchmark with Multimodal Large Language Models

Graphical User Interface (GUI) automation relies on accurate GUI grounding.However, obtaining large-scale, high-quality labeled data remains a key challenge, particularly in desktop environments like Windows Operating System (OS).Existing datasets primarily focus on structured web-based elements, leaving a gap in real-world GUI interaction data for non-web applications.To address this, we introduce a new framework that leverages LLMs to generate large-scale GUI grounding data, enabling automated and scalable labeling across diverse interfaces.To ensure high accuracy and reliability, we manually validated and refined 5,000 GUI coordinate-instruction pairs, creating WinSpot-the first benchmark specifically designed for GUI grounding tasks in Windows environments.WinSpot provides a high-quality dataset for training and evaluating visual GUI agents, establishing a foundation for future research in GUI automation across diverse and unstructured desktop environments 1 .

Authors

Institutions

Publication Details

Published
2025-01-01
DOI
https://doi.org/10.18653/v1/2025.acl-short.85
Primary Topic
Speech and dialogue systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

WinSpot: GUI Grounding Benchmark with Multimodal Large Language Models

Dan Zhao, Colby Banbury, Kazuhito Koishida, Hui Zheng et al.
Speech and dialogue systems
article

WinSpot: GUI Grounding Benchmark with Multimodal Large Language Models

Dan Zhao, Colby Banbury, Kazuhito Koishida, Hui Zheng, Tianyi Chen, Yinheng Li
article en

Abstract

Graphical User Interface (GUI) automation relies on accurate GUI grounding.However, obtaining large-scale, high-quality labeled data remains a key challenge, particularly in desktop environments like Windows Operating System (OS).Existing datasets primarily focus on structured web-based elements, leaving a gap in real-world GUI interaction data for non-web applications.To address this, we introduce a new framework that leverages LLMs to generate large-scale GUI grounding data, enabling automated and scalable labeling across diverse interfaces.To ensure high accuracy and reliability, we manually validated and refined 5,000 GUI coordinate-instruction pairs, creating WinSpot-the first benchmark specifically designed for GUI grounding tasks in Windows environments.WinSpot provides a high-quality dataset for training and evaluating visual GUI agents, establishing a foundation for future research in GUI automation across diverse and unstructured desktop environments 1 .

Microsoft (United States) (US), Microsoft Research (United Kingdom) (GB)
Quality Education
Openalex Percentile: Top 90%
Speech and dialogue systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.