Semantic Scholar is a scholarly literature search and discovery engine that uses AI to extract key concepts, citations, and connections from research papers.
Semantic Scholar is an AI-powered academic search engine designed to help researchers, students, and professionals efficiently discover and evaluate scientific literature. It indexes millions of scholarly articles across computer science, biomedicine, and many other disciplines, drawing from journals, conferences, and preprint servers. The platform uses natural language processing and citation analysis to surface the most relevant and influential papers for a given query, going beyond simple keyword matching.
Key features include semantic search that understands the context of queries, citation graphs to trace how ideas evolve, and paper summaries that highlight key contributions and findings. Users can filter results by publication type, venue, author, year, and more, and access structured metadata such as references, citations, and related work. Author profiles aggregate publications, citation counts, and co-author networks to support evaluation of research impact.
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