Research Rabbit
ResearchRabbit is an AI assisted literature discovery tool that helps you find related papers and authors, build citation maps, and track research trends with alerts, offering a free plan with unlimited searches and one project plus an optional RR+ subscription.
Overview
ResearchRabbit is an AI assisted literature discovery tool designed to help researchers move from a few seed papers to a broader view of a field. The site describes workflows for finding related papers, building citation maps, and tracking research trends, and its guides walk through creating collections and exploring connections between papers and authors. This makes it useful for literature reviews, thesis topic exploration, and staying current as a field evolves.
ResearchRabbit publishes a clear pricing page. The Free plan is $0 forever and includes unlimited searches across 280 plus million articles, searching from up to 50 inputs, basic search settings, and one project. An RR+ plan is also listed for users who need more than a single project and expanded settings, which provides a path to scale without switching tools.
In use, the quality of results depends on your starting seeds and how you curate collections. A reliable approach is to add a small set of canonical papers, review suggested related work, and then use citation maps to identify clusters and influential authors. Alerts can help you track updates to a collection over time so you do not re run searches manually.
For teams and labs, confirm collaboration options, export needs, and how it fits with your reference manager workflow. Evaluate it against alternatives by testing discovery breadth, map readability, and whether the tool helps you find both foundational papers and recent work efficiently.
Key features
- Citation maps: Visualize connections between papers so you can see clusters and influential work rather than reading in isolation
- Collections and projects: Save papers into collections and organize them as projects to keep a literature review structured
- Author exploration: Follow authors related to your collection to discover their other papers and see how networks evolve
- Research alerts: Get alerts tied to your collections so new relevant papers are suggested without repeating manual searches
- Seed based discovery: Start from up to 50 input papers in the free plan and expand outward using related work suggestions
- Large coverage claim: The pricing page states searches span 280 plus million articles which helps broad discovery across fields
- Free and RR+ plans: The pricing page lists a $0 forever plan and an RR+ subscription when you need more projects and settings
- Guided tutorials: Official guides walk through collections citation maps and author tracking so new users learn workflows quickly
Best for
- Literature review start: Add a few seed papers then use citation maps to find foundational work and recent branches quickly
- Thesis topic discovery: Explore clusters around an idea and identify gaps where fewer papers connect or methods are missing
- Author tracking: Follow key authors from your collection to discover their latest publications and related collaborators
- Staying current: Use collection alerts to surface new relevant papers so you keep up with fast moving fields efficiently
- Cross discipline scan: Start with one paper then expand to adjacent domains to find methods you can transfer to your project
- Reading list curation: Build a structured reading list inside a project so you can prioritize what to read and why it matters
- Grant background prep: Map a topic area to spot influential citations and summarize where your proposal adds novelty clearly
- Lab onboarding: Share a curated collection and map view with new lab members so they learn the landscape and key papers faster
Capabilities
Citation map views
Generate visual citation maps that show how papers connect and cluster over time. Use the map to spot influential work and follow branches without manually chasing references.
Collections and projects
Organize papers into collections and projects so a literature review stays structured. Useful for separating themes methods or chapters and for tracking what you have already read.
Alerts and tracking
Set alerts for a collection so the tool suggests new papers relevant to your saved set. This supports ongoing monitoring of a field without repeated search sessions.
Seed based discovery
Start from a set of seed papers and expand outward through related work and author networks. Best for exploring a topic quickly then narrowing to a focused reading list.
Frequently Asked Questions
What is the starting price for ResearchRabbit?
ResearchRabbit lists a Free plan priced at $0 forever, including unlimited searches and one project. If you outgrow one project, the pricing page also lists an RR+ subscription with additional capacity.
Does ResearchRabbit integrate with reference managers?
ResearchRabbit focuses on discovery and mapping. If your workflow depends on Zotero, Mendeley, or BibTeX export, check the current product guides and test export or sync options before committing to a team process.
How do citation maps help compared to keyword search?
Citation maps show how papers connect through citations and related work. This can reveal clusters and influential authors that keyword search misses, especially when terminology varies across subfields or changes over time.
What skills are needed to get good results?
You do not need ML expertise, but you do need curation skills. Start with high quality seed papers, prune irrelevant suggestions, and keep collections focused so alerts and recommendations stay useful.
How should I evaluate privacy and data handling?
You will share reading interests and paper lists, which can be sensitive in competitive research. Review the privacy policy and account controls, and avoid uploading unpublished confidential manuscripts unless terms explicitly allow it.
