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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

Scientific Article Summarization Using Citation-Context and Article's Discourse Structure
2017 Arman Cohan, Nazli Goharian

Spatial Modeling in Environmental and Public Health Research
2010 Michael Jerrett, Sara Gale, Caitlin Kontgis

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

A synthesis of recent analyses of human resources for health requirements and labour market dynamics in high-income OECD countries
2016 Gail Tomblin Murphy, Stephen Birch, Adrian MacKenzie et al.

Development and Evaluation of a UAV-Photogrammetry System for Precise 3D Environmental Modeling
2015 Mozhdeh Shahbazi, Gunho Sohn, Jérôme Théau et al.

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

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

TurkPrime.com: A versatile crowdsourcing data acquisition platform for the behavioral sciences
2016 Leib Litman, Jonathan Robinson, Tzvi Abberbock

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

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.