Despite the central importance of research papers to scientific progress, they can be difficult
to read. Comprehension is often stymied when the information needed to understand a …

Research consumption has been traditionally limited to the reading of academic papers—a
static, dense, and formally written format. Alternatively, pre-recorded conference …

Scholars need to keep up with an exponentially increasing flood of scientific papers. To aid
this challenge, we introduce Scim, a novel intelligent interface that helps experienced …

Extracting underlying data from rasterized charts is tedious and inaccurate; values might be
partially occluded or hard to distinguish, and the quality of the image limits the precision of …

When reading a scholarly paper, scientists oftentimes wish to understand how follow-on
work has built on or engages with what they are reading. While a paper itself can only …

Graph databases capture richly linked domain knowledge by integrating heterogeneous
data and metadata into a unified representation. Here, we present the use of bespoke …

Documents often have paragraphs packed with numbers that are difficult to extract,
compare, and interpret. To help readers make sense of data in text, we introduce the …

Document description languages such as LaTeX are used extensively to author scientific
and technical documents, but editing them is cumbersome: code-based editors only provide …

We introduce RealitySummary, a mixed reality reading assistant that can enhance any
printed or digital document using on-demand text extraction, summarization, and …

Inferential statistics are typically reported using p-values (NHST) or confidence intervals on
effect sizes (estimation). This is done using a range of styles, but some readers have …