August 11, 2025
The GIST Eye-tracking tech achieves 90% accuracy in detecting readers' intent 
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Researchers from the Faculty of Data and Decision Sciences at the Technion have developed a technology capable of identifying various aspects of a reader's interaction with a text that is based solely on their eye movements.
The team's findings were presented at Association for Computational Linguistics, a conference in the field of Natural Language Processing (NLP) in Vienna. The research was led by doctoral student Omer Shubi, together with master's student Cfir Hadar, under the supervision of Dr. Yevgeni Berzak.
People read texts with different goals. Whether it's a novel, a cooking recipe, a newspaper article, or a scientific paper, each type of text can be approached with various intentions. Two common reading goals are general comprehension (regular reading) and information search.
The researchers developed computational models that combine eye-tracking with text processing. These models can accurately detect a reader's purpose with approximately 90% accuracy, and nearly 80% accuracy within just two seconds from the moment the reading started.
According to Dr. Berzak, "This study is part of a broader research program in which we are developing AI models that infer, in real time and from eye movements alone, key aspects of the reader's linguistic knowledge, their interaction with the text, the difference between a first and a second reading, the readability of a given text, and even the specific information the reader is seeking.
"These studies pave the way for new methods in assessing linguistic knowledge, personalizing texts according to the reader's linguistic and reading proficiency, improving accessibility to textual information for various populations, and more."
Eye-tracking technologies are becoming increasingly widespread, affordable, and accurate, with some now available on common devices like iPads and smartphones. The researchers hope these developments will accelerate the adoption of their models, benefiting both users and content providers in fields such as education, government, and media.
Dr. Yevgeni Berzak, a faculty member in the Faculty of Data and Decision Sciences and head of the Language, Computation, and Cognition Lab, joined the Technion in 2021 after completing his Ph.D. and postdoctoral research at MIT.
More information: Omer Shubi et al, Decoding Reading Goals from Eye Movements, Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (2025). DOI: 10.18653/v1/2025.acl-long.280
Journal information: arXiv Provided by Technion – Israel Institute of Technology Citation: Eye-tracking tech achieves 90% accuracy in detecting readers' intent (2025, August 11) retrieved 11 August 2025 from https://techxplore.com/news/2025-08-eye-tracking-tech-accuracy-readers.html This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.
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