AI-Powered Literature Mapping Tools

Are these Generative AI tools? Not exactly.

These tools use AI-powered algorithms to help you explore how research papers are connected — through citation networks, topic similarity, and author networks.

They don’t generate text like ChatGPT or Copilot. Instead, they generate visual maps of related research or recommend papers based on patterns in academic data.

Some tools in this space — such as Scite Assistant  — are starting to include Generative AI features like summaries or question answering.

But the core mapping tools — Research Rabbit, Connected Papers, Litmaps, and Inciteful — use AI for discovery, not for writing or summarising.

Here are four of the most common mapping platforms:

Research Rabbit

• What it does: Builds visual maps of citation networks, co-author networks, and publication timelines.
• Best for: Exploring research networks from a “seed paper.”
• Standout feature: Dynamic, interactive citation and co-author graphs.
• Limits: Coverage based on Microsoft Academic Graph, not updated since 2021.
• Freemium model: Completely free for individual use (no paid tier). Offers collaboration features and Zotero/BibTeX export. 
• Website: researchrabbit.ai

Connected Papers

• What it does: Generates a visual map of papers related to a chosen starting paper based on semantic similarity.
• Best for: Quickly identifying related work around a core paper.
• Standout feature: Easy-to-read semantic paper map starting from one “seed” paper.
• Freemium model: Free with ~5 maps per month. Paid tiers ($5–15/month) provide unlimited maps and additional features.
• Website: connectedpapers.com

Litmaps

• What it does: Tracks research over time using timeline-based maps; allows annotations, sharing, and alerting.
• Best for: Ongoing research tracking, mapping developments over time, and collaborative mapping.
• Standout feature: Timeline-based maps with export and sharing features.
• Freemium model: Free plan allows a small number of inputs and maps with limited alerts. Pro plan (around $8–10/month) offers unlimited maps, alerts, and collaboration features, with Team/Enterprise options available.
• Website: litmaps.com

Inciteful

• What it does: Analyses citation paths and helps find influential, interdisciplinary, or “bridge” papers.
• Best for: Finding connections between research areas and spotting key papers that link topics.
• Standout feature: Citation pathfinding — showing how two papers are connected. Also supports batch import of seed papers and advanced customisation using SQL.
• Freemium model: Free to use for paper discovery and citation pathfinding, with options for batch seed imports. Documentation is limited, and no clear paid tier is advertised.
• Website: inciteful.xyz

Tip: Not sure how these tools compare to other academic search tools like LibrarySearch or Web of Science? Visit our Search and Discovery Tools page to learn how different search tools work — and when to use each one.

Tip: These tools are designed for exploration. For precise, systematic searching, use LibrarySearch, Scopus, or Web of Science. See our Search and Discovery Tools guide to learn more.

Many AI tools are freemium, meaning they offer a free version with limited features, while paid versions unlock higher search limits, export options, or collaboration tools.

You do not need to pay to succeed. Everything you need for your studies can be done using the free features of these tools, plus the resources provided by the Library.

These tools do not search the entire academic universe. Most rely on open datasets like Semantic Scholar, OpenAlex, PubMed, or Crossref. This means:

• They may miss paywalled content (e.g., papers in Elsevier, Wiley, Springer, or Taylor & Francis journals).
• Many summarise based on abstracts, not full text.
• They often work better in some fields (STEM, medicine, computer science) than others (humanities, creative industries, or law).
• Book coverage is especially weak — use [LibrarySearch] to find academic monographs, edited collections, and eBooks.

Important: Do not upload unpublished research, identifiable participant data, or grant applications to any mapping tool.

Unlike structured databases like Scopus or Web of Science, AI-powered mapping tools are not fully reproducible.

• Results may vary. Two users can get different suggestions or maps from the same input.
• These tools rely on dynamic AI models, citation data, and changing algorithms.
• This means you cannot use these tools for systematic reviews where reproducibility is essential.

Tip: If you're using one of these tools for scoping, note the date and the seed paper or query you used, so you can document your process transparently.

Mapping tools are powerful aids for exploration, but they do not replace:

• Formal literature review methods (systematic searching, PRISMA, etc.)
• Critical reading of full papers
• Verification of peer-reviewed status
• Evaluation of source credibility