We were frustrated by the experience of reading machine learning papers on screens (particularly phones/tablets). There are lots of good tools for authoring HTML papers (Distill, Authorea, etc) but nothing that deals with the vast number of PDF papers that already exist.
So, we built Arxiv Vanity: a site that renders Arxiv papers as web pages. It’s still pretty janky, but for the papers that do render correctly, the experience is so much better than reading a PDF. For example:
So, we built Arxiv Vanity: a site that renders Arxiv papers as web pages. It’s still pretty janky, but for the papers that do render correctly, the experience is so much better than reading a PDF. For example:
https://www.arxiv-vanity.com/papers/1705.04085v3/
https://www.arxiv-vanity.com/papers/1708.00884/
https://www.arxiv-vanity.com/papers/1705.06031v2/
The source for the LaTeX to HTML renderer is on GitHub[0]. It’s built on Pandoc[1] and Distill.pub’s template[2].
[0] https://github.com/arxiv-vanity/engrafo
[1] https://pandoc.org
[2] https://github.com/distillpub/template