Semantic Scholar

Semantic Scholar is a free, AI-driven academic search engine developed by the Allen Institute for AI (AI2). Its goal is to make scientific literature more accessible and useful by using machine learning, natural language processing, and citation analysis to surface the most relevant research quickly.

Key Features

• AI-powered search and ranking
  Surfaces papers based on relevance, influence, and semantic understanding—not just keyword matching.
• Smart paper summaries
  Highlights key contributions, methods, datasets, and citations.
• Citation-based insights
  Tracks influential citations, co-citations, and citation graphs.
• Author profiles
  Automatically generated profiles with publication lists, h-index estimates, co-authorship networks, and research topics.
• Topic pages
  AI-curated overviews of fields, key authors, landmark papers, and emerging research.
• Filters & discovery tools
  Filter by fields of study, publication type, venue, year, and open-access status.
• Paper recommendations
  Personalized suggestions based on reading history and saved libraries.
• Open access integration
  Links to PDFs, preprints, and repositories when available.

Who Can Use This

• Researchers searching for the most relevant papers with less noise than Google Scholar.
• Students learning a new field through topic pages and paper summaries.
• Institutions & labs tracking researchers, topics, and publication impact.
• Literature review workflows using saved libraries, alerts, and citation tracing.