Semantic Scholar
What is Semantic Scholar?
Semantic Scholar is a machine-learning search platform for researchers that surfaces scientific literature with summaries, citation context, and reading tools. It combines Search, TLDRs, Highly Influential Citations, Cite, Library, Research Feeds, Alerts, and Ask This Paper, and it powers products such as Litmaps, Connected Papers, Stateoftheart AI, Sourcely, and Yomu. The Academic Graph API exposes authors, papers, citations, venues, recommendations, and datasets for developers.
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At a glance
- Semantic Scholar is best for researchers who need faster paper discovery and contextual reading.
- Yes — Semantic Scholar Academic Graph API provides on-demand data about authors, papers, citations, venues, and more.
What does Semantic Scholar do?
Semantic Scholar uses machine learning to search and surface scientific literature with more context than a plain keyword index. It helps readers find relevant papers, scan them faster with TLDRs, and jump to influential citations, while the citation flow supports BibTex, MLA, APA, and Chicago formats. The reading experience also extends into Semantic Reader, which adds in-line citation cards, a table of contents, and save-to-library workflows so researchers can move from discovery to reading without losing context. Behind the scenes, Semantic Scholar indexes over 200 million academic papers and the site search spans 234,936,038 papers across all fields of science. Its API adds programmatic access to authors, papers, citations, venues, recommendations, and datasets, and the service is built for developers as well as readers. The platform is based at Ai2, and customer examples include Litmaps and Connected Papers, which use the underlying scholarly data to power their own products.
Why use Semantic Scholar?
- Its search combines filters, TLDRs, and influential-citation signals so readers can triage papers faster.
- Semantic Reader adds in-line context, table-of-contents navigation, and library-aware citations for smoother reading.
- The Academic Graph API gives developers on-demand scholarly data instead of forcing manual scraping.
- It indexes over 200 million papers, giving buyers broad coverage across science rather than a narrow subject slice.
- The platform is backed by Ai2 and used by products like Litmaps and Connected Papers, which signals ecosystem maturity.
Who is Semantic Scholar for?
- Academic researchers who need to find relevant papers without wading through long citation lists.
- Graduate students who want quick summaries and organized reading lists for literature reviews.
- Developers building scholarly apps who need programmatic access to papers, citations, and venues.
- Librarians and research support staff who help users discover and manage scientific literature.
- Research teams who want alerts, feeds, and saved-paper workflows to stay current.
What are Semantic Scholar's key features?
Search
Search over 234,936,038 papers and over 200 million academic papers, with filters for fields like Biology, Computer Science, Medicine, Physics, and Psychology.
TLDRs
Read short paper summaries for most English-language arXiv papers in computer science fields, helping you judge relevance faster before opening the full text.
Highly Influential Citations
Surface citation context from the Semantic Scholar Academic Graph, so you can spot papers that shaped a field instead of counting citations alone.
Cite
Generate citations in BibTex, MLA, APA, or Chicago formats, reducing manual formatting work when you move from reading to writing.
Library
Save papers to your library and organize them for later review, which helps keep sources together across research sessions and projects.
Research Feeds
Track trending papers, top viewed papers, top saved papers, and top influential papers, so you can monitor what is gaining attention.
Alerts
Set email alerts for new papers and updates, letting you follow topics and authors without repeatedly checking the site.
Ask This Paper
Use AI to ask questions about a paper, combining paper content with Semantic Scholar data to speed up comprehension and note-taking.
What does Semantic Scholar integrate with?
- BibTex
- MLA
- APA
- Chicago
- Zotero
- Open Athens
- X
- OpenAI
- ChatGPT
- Google Scholar
- Hypothesis
What are Semantic Scholar's use cases?
Literature reviews for grad students
Graduate students use Semantic Scholar to turn a broad topic into a manageable reading list, using Search to find relevant papers fast and TLDRs to decide what deserves a full read. They then Save to Library and use Cite to keep sources organized for a thesis or seminar paper.
Paper discovery for researchers
Academic researchers use Semantic Scholar to move beyond long citation chains and surface the most relevant work, using Highly Influential Citations and Topic pages to spot papers that shaped a field. Alerts and Research Feeds help them stay current as new studies appear.
Scholarly app data access
Developers building scholarly apps use Semantic Scholar to power paper search and citation features programmatically, using the Academic Graph API to retrieve papers, authors, venues, and citations on demand. They can also pull structured data that supports recommendations and discovery workflows.
Research support discovery
Librarians and research support staff use Semantic Scholar to help patrons find scientific literature quickly, combining Search with Ask This Paper to answer follow-up questions about a paper's content. Semantic Reader and note taking features make it easier to guide users through dense articles.
How does Semantic Scholar work?
- Start with Search to enter a paper title, topic, or author, then narrow results with Topics and the Academic Graph to surface the most relevant scientific literature.
- Open a paper and scan TLDRs, Highly Influential Citations, and Citations Cards to judge relevance quickly before committing to a full read.
- Save promising papers to Library, then use Research Feeds and Alerts to track new publications, trending papers, and updates in your area.
- Read with Semantic Reader, using showing, note taking, and Annotate and show to capture key passages and build a reusable study trail.
- Use Cite, Personalized In-line Citations, and supported formats like BibTex, APA, MLA, or Chicago to export references and keep writing workflows moving.
Frequently asked questions
What is Semantic Scholar?
Semantic Scholar is a machine-learning search platform for researchers that surfaces scientific literature with summaries, citation context, and reading tools. It combines Search, TLDRs, Highly Influential Citations, Cite, Library, and Ask This Paper, and it powers products such as Litmaps and Connected Papers. The Academic Graph API exposes authors, papers, citations, venues, recommendations, and datasets for developers.
What is Semantic Scholar used for? Who is it for?
Semantic Scholar is used for Search, TLDRs, and Highly Influential Citations. It's built for Academic researchers, Graduate students, and Developers building scholarly apps.
Does Semantic Scholar have an API and what does it integrate with?
Semantic Scholar Academic Graph API provides on-demand data about authors, papers, citations, venues, and more. It integrates with BibTex, MLA, APA, Chicago, Zotero, and 8 more.
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