Semantic Scholar is a free, AI-powered academic search engine and research tool developed by the Allen Institute for AI (AI2). Launched in 2015, the platform indexes over 200 million academic papers across all fields of science, including computer science, biomedical sciences, physics, mathematics, social sciences, and humanities, sourced from publishers, preprint servers, and open access repositories. Semantic Scholar uses natural language processing and machine learning to understand the content and context of academic papers, enabling more intelligent search and discovery than traditional keyword-based academic databases. The platform's key AI features include TLDR summaries that provide one-sentence AI-generated overviews of paper content, semantic search that understands the meaning behind queries to surface relevant papers even when they use different terminology, and citation context analysis that shows how a paper has been cited and in what context by subsequent research. Semantic Scholar also provides the Semantic Reader, an augmented reading interface that enhances the paper reading experience with inline definitions, citation cards, and figure references. The platform generates author profiles with publication histories, citation metrics, h-index calculations, and co-author networks. Its Research Feed feature uses machine learning to recommend new papers based on a user's research interests and reading history. Semantic Scholar offers the Semantic Scholar Academic Graph API, one of the largest open academic knowledge graphs, which researchers and developers can use to build applications on top of the platform's data. The platform is entirely free to use, supported by the Allen Institute for AI as part of its mission to advance AI for the common good. There are no premium tiers or paywalls for any of Semantic Scholar's features.

AI Document Analysis

Semantic Scholar's Semantic Reader provides AI-powered document analysis features that enhance the reading experience for academic papers. It offers inline term definitions, citation context cards showing how referenced papers are relevant, figure analysis, and structural navigation, helping readers understand complex academic documents more efficiently.

AI Knowledge Bases

Semantic Scholar maintains one of the largest open academic knowledge bases in the world, with its Semantic Scholar Academic Graph containing over 200 million papers, citation relationships, author information, and topic classifications. This structured knowledge base is freely accessible through an API, serving as a foundation for academic research tools and applications.

AI Research Tools

Semantic Scholar provides essential AI research tools including intelligent paper discovery, citation context analysis, author profiling, and personalized research feeds. Researchers use it to track citations, discover related work, identify influential papers in their field, and stay current with new publications through AI-powered recommendations based on their research interests.

AI Search Engines

Semantic Scholar is a leading AI-powered academic search engine that uses natural language processing to understand the meaning behind research queries and surface relevant papers from a corpus of over 200 million publications. Its semantic search capabilities go beyond keyword matching to find conceptually related research across all scientific disciplines.

AI Summarizers

Semantic Scholar offers AI-generated TLDR summaries that provide concise, one-sentence overviews of academic papers, enabling researchers to quickly assess the relevance of papers without reading full abstracts. This summarization feature applies across its entire corpus of over 200 million papers, dramatically accelerating the literature scanning process.