Five papers,
every morning.
Perceptum is a daily reading habit for people who want to keep up with machine learning, statistics, and signal-processing research without spending the first hour of every morning sorting through arXiv.
It is guided by Percepti, our AI research editor: a small editorial layer that ranks the day's papers, writes the briefings, and helps you notice which papers deserve the paper-length version of your attention.
A daily arXiv summary page has to do two jobs at once. It has to be fast enough to read before a standup, and serious enough that a technical reader can tell whether a paper is worth opening. Perceptum is built around that tension. It ranks new papers, keeps the current daily top five and weekly top twenty-five fresh, and summarizes each selected paper at three levels of detail.
Percepti does the first pass like a tireless research assistant with an editor's taste. It looks at author signal, topic fit, early citation context, reference density, and practitioner buzz, then turns the selected papers into plain-English summaries. The rankings are meant to be useful, not final. They are a starting point for attention.
Beginner summaries explain the problem and why it matters. Intermediate summaries read like notes from a sharp colleague. Expert summaries spend more time on method, result, caveats, and what the paper builds on. You can skim the headline, read the one-line thesis, or settle into the full five-minute version.
The product is intentionally small. There is no endless archive to browse and no pressure to clear a queue. Papers age out after about a week, because the homepage is meant to feel like a fresh research desk, not a reference library. Shared paper links still work while the paper is fresh, but discovery is focused on the pages where readers can subscribe and return tomorrow.
A paper should earn your attention before it asks for your afternoon.
Perceptum starts with the question a busy technical reader is actually asking: what changed, why should I care, how did they test it, and what should I distrust? The daily page answers those questions before linking out to arXiv.
How it works
- 01We gather new studies from arXiv
- 02We rank papers by author signal, topic fit, citations, reference density, and practitioner buzz
- 03We summarize the papers that look most worth your time
- 04You get the top papers for the day or week, in your inbox or on the site
Built by Dusan Kovacevic. Questions, suggestions, or papers we should be ranking better? [email protected].