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News: Check out our newer demo at Paper To HTML.

Welcome to SciA11y!

This is an experimental prototype created by Semantic Scholar. It provides access to 1.5M open access scientific documents in accessible HTML format. Our system uses machine learning techniques to extract the semantic content of scientific papers and formats it in HTML for easier reading. Because of our reliance on statistical machine learning techniques, some errors are inevitable. We will continue to improve upon our models and would love to hear your feedback in the meantime. The papers included in this demo come from a static dataset; all papers have CC (non-ND) licenses and were published in or before April 2020. More about this prototype...

You can also upload your own PDF, which we process and render in HTML for reading. You can try this functionality here.

Example papers

Deep Learning for Computer Vision: A Brief Review
2018 Athanasios Voulodimos, Nikolaos Doulamis, Anastasios Doulamis et al.

Spatial Representation of the Workspace in Blind, Low Vision, and Sighted Human Participants
2018 Jacob S. Nelson, Irene A. Kuling, Monica Gori et al.

Improved Transition-Based Parsing by Modeling Characters instead of Words with LSTMs
2015 Miguel Ballesteros, Chris Dyer, Noah A. Smith

Vaccine Adjuvants: from 1920 to 2015 and Beyond
2015 Alberta Pasquale, Scott Preiss, Fernanda Silva et al.

Risk Factors and Preventions of Breast Cancer
2017 Yi-Sheng Sun, Zhao Zhao, Zhang-Nv Yang et al.

Responses of Marine Organisms to Climate Change across Oceans
2016 Elvira S. Poloczanska, Michael T. Burrows, Christopher J. Brown et al.

The global burden of congenital heart disease
2013 Julien IE Hoffman

Mendelian randomization of blood lipids for coronary heart disease
2014 Michael V. Holmes, Folkert W. Asselbergs, Tom M. Palmer et al.

Life cycle assessment of construction and renovation of sewer systems using a detailed inventory tool
2016 Serni Morera, Christian Remy, Joaquim Comas et al.

Assessing the utility of social media as a data source for flood risk management using a real‐time modelling framework
2017 L. Smith, Q. Liang, P. James et al.

Preprint

To find out more about how we created this prototype, please read our preprint. Accessible PDF available here.

Team

Feedback

Please address questions or feedback to Lucy Lu Wang or Jonathan Bragg.