Semanticscholar

Semantic Scholar is a free, AI-powered research tool for scientific literature, built at the Allen Institute for AI (Ai2). It lets you search and explore papers from all fields of science, with a large searchable collection of scientific work.

Use it to find relevant research faster and understand connections between papers. The platform highlights papers using AI-driven analysis and provides helpful ways to explore results across fields, dates, authors, journals, and more.

Developers can also use Semantic Scholar’s improved API, which includes paper search along with better documentation and increased stability. You can also try Semantic Reader in beta for select papers, an augmented reading experience designed to make papers more accessible and richly contextual.

Semantic Scholar also supports sustainability efforts through “Green AI” principles—focusing on making deep learning study less dependent on the deepest pockets while improving efficiency and inclusivity in research.

How many papers can I search on Semantic Scholar?

You can search hundreds of millions of papers across all fields of science, including 236,352,711 papers shown on the site.

Is Semantic Scholar free to use?

Yes. Semantic Scholar is free to use as an AI-powered research tool.

What does Semantic Reader do?

Semantic Reader is an augmented reader in beta that aims to make scientific papers more accessible and richly contextual, with enhanced navigation for select papers.

Does Semantic Scholar offer an API for developers?

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

What are some common benefits when using Semantic Scholar?

It helps you locate relevant and influential papers, explore relationships between research, and refine discovery with filters and recommendations.

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

Because the tool relies on AI processing of scientific content, it can sometimes misinterpret text or miss nuance, and coverage may be incomplete for every paper.