Research Rabbit
AI paper discovery
Deep Dive Review
Research Rabbit is an AI-powered literature mapping tool. You add seed papers and it builds an interactive citation graph, recommends related work, and tracks new publications - turning paper discovery into a visual, navigable network across fields like AI, medicine, and physics.
Pros & Cons
- See review
- See review
Key Features
- Seed-paper based recommendations
- Interactive citation graphs
- Similar paper & author tracking
Use Cases
- Literature review & discovery
- Citation network visualization
- Staying updated on new papers
Target Audience
- Researchers
- PhD students
- Academic librarians
Quick Overview
| Category | research |
| Pricing | Free |
| Tags | discovery, papers, citations |
Go to Research Rabbit Website →
Frequently Asked Questions
How does Research Rabbit recommend papers?
Research Rabbit analyzes the citation graph around your seed papers - who they cite and who cites them - and surfaces similar or related work ranked by relevance, far beyond simple keyword matching.
Can I collaborate on collections in Research Rabbit?
Yes. You can organize papers into collections and share them with collaborators, which makes systematic reviews and lab-wide reading lists much easier to coordinate.
How does Research Rabbit compare to Semantic Scholar or Connected Papers?
Semantic Scholar is a search engine, and Connected Papers builds single-purpose graph visualizations. Research Rabbit combines recommendation, visualization, and ongoing tracking in one free tool designed around your library.