Semantic paper search
Runs semantic retrieval using SPECTER2 embeddings trained for scientific papers, so queries can match papers by meaning even when the wording differs.
Cito is a semantic search service for academic papers. Find research by meaning, with keyword and hybrid search, structured metadata, saved papers, and API keys.
Cito is a semantic search service for academic papers. It is designed to help people find research by meaning rather than by exact keywords, and it covers a corpus of roughly 148 million papers from Semantic Scholar and OpenAlex data.
The product exposes a programmatic API and search interface that combine semantic retrieval with keyword matching. Queries can be run against Cito's own self-hosted indexes, which makes results deterministic for the same query and corpus snapshot and avoids relying on upstream API rate limits at search time.
Runs semantic retrieval using SPECTER2 embeddings trained for scientific papers, so queries can match papers by meaning even when the wording differs.
Combines classic BM25 full-text matching over titles and abstracts with semantic retrieval, then merges the rankings with reciprocal-rank fusion.
Can run either retriever on its own with mode=semantic or mode=keyword, which lets users narrow the search strategy when needed.
Searches its own self-hosted indexes rather than calling a third-party API at query time, which keeps results reproducible and avoids inherited upstream rate limits.
Returns structured paper metadata, including title, authors, venue, publication date, DOI, citation count, abstract when available, and an open-access PDF link when one exists.
Supports user accounts for saved papers, API keys, and usage viewing through GitHub sign-in or an existing API key.
Researchers can start from a landmark paper or a concept and surface related work even when the relevant papers use different terminology.
Developers can query the API from their own tools or workflows when they need programmatic access to academic search results and metadata.
Teams building research-facing products can reuse the searchable corpus and response metadata in commercial contexts, while keeping the required attribution string in republished results.
Users who need exact terms, acronyms, or author jargon can switch to keyword search, or use the hybrid mode to balance precise matching with semantic recall.
Cito is a search service for academic literature. It supports semantic search, keyword search, or a fused search mode that combines both retrievers.
The source documentation says Cito returns title, authors, venue, publication date, DOI, citation count, an abstract when available, and a direct open-access PDF link when one exists.
Yes. The licensing page says Cito can be used in commercial products, research, and publications, with the requirement to keep the attribution string that every API response carries: “Data from Semantic Scholar” when republishing results.
Cito has an account area for signing in with GitHub, saving papers, creating API keys, and viewing usage. It also says an API key can be used to view your account.
Cito does not proxy or re-host full text. PDF links point to the original publisher or repository, and access to the PDF is governed by that source's terms.
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