adrianadunn's comments

adrianadunn | 4 years ago | on: SciA11y: Improving the Accessibility of Scientific Documents

The majority of scientific papers are distributed in PDF, which pose challenges for accessibility, especially for blind and low vision (BLV) readers.

SciA11y incorporates several machine learning models to extract the content of scientific PDFs and render this content as accessible HTML, with added novel navigational features to support screen reader users.

Preprint: https://arxiv.org/abs/2105.00076

Blog post: https://medium.com/ai2-blog/scia11y-improving-the-accessibil...

Demo: https://scia11y.org/

Disclosure: I work for the Semantic Scholar team at the Allen Institute for AI, the nonprofit research organization working on SciA11y.

adrianadunn | 4 years ago | on: Semantic Reader: Show Reference Abstracts in Context, and More

Adriana here from the Semantic Scholar team at AI2.

Thanks for your interest in the Semantic Reader beta! We're actively testing and developing new features and welcome your feedback (https://www.surveymonkey.com/r/Q5K2XPK).

adrianadunn | 5 years ago | on: Introducing TLDRs on Semantic Scholar

Adriana here from the Semantic Scholar team at the Allen Institute for AI. A few cliff notes:

- Now available in beta for ~10M computer science papers on Semantic Scholar [1]

- This feature auto-generates extreme, single-sentence summaries of scientific papers. Super easy to skim, especially on mobile.

- The TLDR Model powering this new feature was built by our Research team; read the paper for more details. [2]

We're seeking feedback from computer scientists. Comment here, or you can email me at adrianad [at] allenai.org

[1] semanticscholar.org

[2] semanticscholar.org/paper/TLDR%3A-Extreme-Summarization-of-Scientific-Documents-Cachola-Lo/3502a542b2e98d9094e1880a30f652d4170b9534

adrianadunn | 5 years ago | on: How to seriously read a scientific paper

I work on the Semantic Scholar team at the Allen Institute for AI (allenai.org). We're working on solving the problems described in the post.

We're investing considerable effort into making it easier for researchers to find and consume scientific literature. Our team is made up of engineers and researchers who have felt the pain points firsthand and are very motivated to design and build solutions that fix them. Our software is free to use, and always will be.

Our search engine uses things like citation intent, citation influence, and figure and table extraction to make filtering through papers easier. We’re also currently prototyping an augmented reading experience that aims to embed contextual information directly into the reading experience so that it's easier to consume and comprehend academic literature. Give it a try: semanticscholar.org.