WebClick is a high-quality web understanding benchmark dataset for evaluating the ability of multimodal models and agents to understand web interfaces, interpret user commands, and take precise actions in digital environments. The dataset contains 1,639 English webpage screenshots from more than 100 websites, which are accompanied by accurately annotated natural language instructions and pixel-level click targets.

Dataset structure:

• agentbrowse(36%): Pages encountered by the SurferH agent when solving WebVoyager's Web retrieval tasks
• humanbrowse (31.8%): Pages and elements that humans interact with when performing everyday tasks (e-shopping, travel planning, personal organization)
• calendars (32.2%): Focuses on a specialized subset of calendar interfaces, which is a known challenge for UI comprehension models

Citation

@dataset{hcompany2025uinavigate,
author = {H Company Research Team},
title = {WebClick: A Multimodal Localization Benchmark for Web-Navigation Models},
year = {2025},
publisher = {H Company},
}
@misc{andreux2025surferhmeetsholo1costefficient,
title={Surfer-H Meets Holo1: Cost-Efficient Web Agent Powered by Open Weights},
author={Mathieu Andreux and Breno Baldas Skuk and Hamza Benchekroun and Emilien Biré and Antoine Bonnet and Riaz Bordie and Matthias Brunel and Pierre-Louis Cedoz and Antoine Chassang and Mickaël Chen and Alexandra D. Constantinou and Antoine d'Andigné and Hubert de La Jonquière and Aurélien Delfosse and Ludovic Denoyer and Alexis Deprez and Augustin Derupti and Michael Eickenberg and Mathïs Federico and Charles Kantor and Xavier Koegler and Yann Labbé and Matthew C. H. Lee and Erwan Le Jumeau de Kergaradec and Amir Mahla and Avshalom Manevich and Adrien Maret and Charles Masson and Rafaël Maurin and Arturo Mena and Philippe Modard and Axel Moyal and Axel Nguyen Kerbel and Julien Revelle and Mats L. Richter and María Santos and Laurent Sifre and Maxime Theillard and Marc Thibault and Louis Thiry and Léo Tronchon and Nicolas Usunier and Tony Wu},
year={2025},
eprint={2506.02865},
archivePrefix={arXiv},
primaryClass={cs.AI},
url={https://arxiv.org/abs/2506.02865},
}