Semantic Scholar Product Overview

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Semantic Scholar·semanticscholar.org/product

Credibility Rating

4/5

High(4)

High quality. Established institution or organization with editorial oversight and accountability.

Rating inherited from publication venue: Semantic Scholar

Semantic Scholar is a free academic search tool useful for AI safety researchers tracking literature; not specific to AI safety but widely used in the field for literature discovery and citation analysis.

Metadata

Importance: 35/100tool pagetool

Summary

Semantic Scholar is an AI-powered scientific literature search and discovery platform covering over 214 million papers. It offers features like AI-generated TLDRs, influential citation detection, personalized research feeds, and library management tools to help researchers find and organize relevant work.

Key Points

•Indexes 214+ million papers across all scientific fields with filters for journals, authors, publication type, and date range
•TLDRs provide AI-generated ultra-short summaries for ~60 million papers in CS, biology, and medicine
•Highly Influential Citations feature uses ML to identify papers with significant impact on citing works
•Library tools allow organizing papers into folders, bulk citation export, and sharing with collaborators
•AI-powered Research Feeds generate personalized paper recommendations based on saved library folders

Cited by 1 page

Page	Type	Quality
AI-Era Epistemic Infrastructure	Approach	59.0

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# Our Product

Experience a Smarter Way to Search and Discover Research

Scholars like you make impactful, groundbreaking research work every single day around the world. We are here to support you by providing a better way to search and discover scientific knowledge.

![Illustration: Papers being accelerated by Semantic Scholar](https://cdn.prod.website-files.com/605236bb767e9a5bb229c63c/60d37af64aa9cd061f711154_about_us_discovery_v3-01.png)

![](https://cdn.prod.website-files.com/605236bb767e9a5bb229c63c/6274192c8e3f6111c5eab05f_accelerating-science-01.svg)

# Search

## Find Relevant Research

Search over 214 million papers from all fields of science, with filters such as journals and conferences, authors, publication types, and date range.

#### Scan Papers Faster with TLDRs

![A screen shot of the paper "Construction of the Literature Graph in Semantic Scholar" Ammar et. al 2018, with the TLDR: "This paper reduces literature graph construction into familiar NLP tasks, point out research challenges due to differences from standard formulations of these tasks, and report empirical results for each task."](https://cdn.prod.website-files.com/605236bb767e9a5bb229c63c/632b6e3c984318860a990804_tldr.png)

Identifying the right papers for you can be time-consuming. To save some time, look for TLDRs (Too Long; Didn't Read) on search results pages.

‍ [TLDRs](https://www.semanticscholar.org/product/tldr) are super-short summaries of the main objective and results of a paper, generated using expert background knowledge and NLP techniques, available for nearly 60 million papers in computer science, biology, and medicine.

#### Check Highly Influential Citations

![Photo of a citation that has been highly influenced by Ammar et. al 2018](https://cdn.prod.website-files.com/605236bb767e9a5bb229c63c/632b705b31efdc0c10711bcd_highly-influenced.png)

Too many citations to wade through? Start with the [Highly Influential Citations](https://www.semanticscholar.org/faq#influential-citations) where the cited publication has a significant impact on the citing publication, determined by a machine-learning model that analyzes factors including the number of citations to a publication and the surrounding context for each.

[Search Now](https://www.semanticscholar.org/)

# Cite

## Cite Any Paper

Any paper you find relevant for your research, select "Cite" on a paper page or in the search results.

A pop-up will offer you the option of multiple citation formats including BibTex, MLA, APA, or Chicago.

![Screenshot of the citation button on Semantic Scholar](https://cdn.prod.website-files.com/605236bb767e9a5bb229c63c/63290ff1477b8824d7905951_cite.png)

![Screenshot of the citation modal on Semantic Scholar](https://cdn.prod.website-files.com/605236bb767e9a5bb229c63c/632914289b5b433c7535c40e_cite-modal.png)

![Illustrated folder with papers and a circle in it](https://cdn.prod.website-files.com/605236bb767e9a5bb229c63c/61de1b6644f08554e9de4a3c_assets-folder-01.svg)

# Li

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