Semanticscholar

Semantic Scholar is a free, AI-powered research tool for scientific literature, built at the Allen Institute for AI (Ai2). It helps you search across all fields of science and explore a very large collection of papers to find relevant work faster.

With Semantic Scholar, you can search tens to hundreds of millions of papers and navigate through results in ways that make connections easier to understand. The platform uses AI-driven analysis to highlight and contextualize papers, helping you explore content by topics, dates, authors, and journals as you build your literature review or research trail.

If you’re a developer, Semantic Scholar also offers an improved API that includes paper search, better documentation, and increased stability—so you can build scholarly applications on top of its research resources.

You can also try Semantic Reader in beta for select papers. Semantic Reader is an augmented reading experience designed to make papers more accessible and richly contextual, with enhanced navigation for those papers.

Pricing is straightforward: Semantic Scholar is free to use. Keep in mind that AI processing of scientific content can sometimes misinterpret text or miss nuance, and coverage may be incomplete for every paper.

How many papers can I search in Semantic Scholar?

You can search on the order of hundreds of millions of papers; the site lists a count of 239,500,957 papers across all fields of science.

Is Semantic Scholar free to use?

Yes. Semantic Scholar is a free, AI-powered research tool for scientific literature.

What is Semantic Reader, and is it available for all papers?

Semantic Reader is an augmented reader in beta that makes select papers more accessible and richly contextual. It’s available for select papers rather than all papers.

Does Semantic Scholar offer an API for developers?

Yes. The improved API includes paper search, better documentation, and increased stability to help you build scholarly applications.

How does Semantic Scholar help me understand relationships between papers?

It uses AI-driven analysis to highlight papers and provide ways to explore content and context across fields, dates, authors, and journals—helping you trace related research.

Are there limitations to the AI-powered search and summaries?

Yes. AI processing can sometimes misinterpret text or miss nuance, and coverage may not be complete for every paper.