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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

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

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

Internet Access by People with Intellectual Disabilities: Inequalities and Opportunities
2013 Darren Chadwick, Caroline Wesson, Chris Fullwood

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.

Modulating proximal cell signaling by targeting Btk ameliorates humoral autoimmunity and end-organ disease in murine lupus
2012 Jack Hutcheson, Kamala Vanarsa, Anna Bashmakov et al.

Multi-domain Neural Network Language Generation for Spoken Dialogue Systems
2016 Tsung-Hsien Wen, Milica Gasic, Nikola Mrksic et al.

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

Biomedical ontology alignment: an approach based on representation learning
2018 Prodromos Kolyvakis, Alexandros Kalousis, Barry Smith 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.