Project - Paper Radar

Introduction

Paper Radar is a minimalist daily AI paper digest that helps me scan the most interesting new research without drowning in the full arXiv firehose.

The live site is here: Paper Radar

Why I Built It

Keeping up with AI research is exciting, but also exhausting. There are too many papers, too many tabs, and not enough signal when I only have a few minutes.

I wanted a small product that could answer three practical questions every day:

Which papers are actually worth my attention?
Can I get different summary depths depending on my energy level?
Can this run as a lightweight static site instead of a heavy full-stack app?

What It Does

Paper Radar publishes a curated list of AI papers with three reading modes:

Expert mode for method details and technical depth
General mode for a faster, professional summary
Lazy mode for a short, punchy takeaway

The result is a reading experience that feels more like a daily research briefing than a raw paper feed.

How It Works

The current workflow is intentionally simple and cheap to run:

Fetch the latest papers from arXiv.
Filter obvious noise with lightweight scripts.
Score and shortlist the most promising papers.
Generate layered summaries for different reading modes.
Publish the result as a static front end.

This project is built with a human-in-the-loop workflow, where scripts handle repetitive work and AI assistance helps with higher-value curation and summarization.

Stack

Next.js 14
TypeScript
Tailwind CSS
Static data files
arXiv as the upstream paper source
NotebookLM-assisted summarization in the current workflow

Kris Shen