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Resources

Resources for the Global Research Community

Semantic Scholar provides the following resources as free services for researchers.

Filter Resources:
DatasetCodeAPICorpusProjectPaper
S2AG API

Providing a reliable source of scholarly data for developers

Programatically search 200 million papers and 74 million authors

f_API

ScholarPhi

AI-Powered Augmented Scientific Reading Application

Augmented scientific reading system developed by AI2, UC Berkeley, and UW

f_Project, f_Code, f_Paper

S2AG Dataset

Semantic Scholar Academic Graph (S2AG) Dataset

Semantic Scholar's records for research papers published in all fields provided as an easy-to-use JSON archive

f_Dataset

DeepFigures

Figure extraction using deep neural nets

Companion code to the paper "Extracting Scientific Figures with Distantly Supervised Neural Networks"

f_Code, f_Paper

SciA11y

Accessible Scientific Reading

The SciA11y system introduces machine learning models to extract the content of scientific PDFs and render it as accessible HTML

f_Project, f_Code, f_Paper

SUPP.AI

AI-curated corpus of supplement and drug interactions

Supp.AI automatically extracts evidence of supplement and drug interactions from the scientific literature and presents them in a corpus of 2,044 supplements, 2,842 drugs and 58,017 interactions

f_Corpus

SPECTER

Document-level Representation Learning using Citation-informed Transformers

repository contains code, link to pretrained models, instructions to use SPECTER and link to the SciDocs evaluation framework

f_Code, f_Paper

CORD-19

Coronavirus Open Research Dataset

CORD-19 is a corpus of academic papers about COVID-19 and related coronavirus research

f_Dataset, f_Paper

S2ORC

Semantic Scholar Open Research Corpus

Corpus for NLP and text mining research over scientific papers

f_Corpus, f_Paper

S2AND

Semantic Scholar Author Name Disambiguation

Our algorithm & evaluation suite for author name disambiguation in scientific literature

f_Code, f_Paper, f_Dataset

SciFact

SciFact dataset and claim verification system

Claim verification system trained on our SciFact dataset

f_Dataset

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Latest News & Updates

Case Study: Iterative Design for Skimming Support

Case Study: Iterative Design for Skimming Support

Oct 6, 2023
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How might we help researchers quickly assess the relevance of scientific literature? Take a closer look at Skimming, Semantic Reader’s latest AI feature, and the collaborative design process behind it.

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Behind the Scenes of Semantic Scholar’s New Author Influence Design

Behind the Scenes of Semantic Scholar’s New Author Influence Design

Aug 17, 2023
5 min read

We released a new version of Author Influence interface to help scholars better discover other scholars in their fields. Here's how we identified user insights and made those design choices.

Cassidy Trier, Evie Cheng, Ashley Lee
Artificial-intelligence search engines wrangle academic literature

Artificial-intelligence search engines wrangle academic literature

Aug 7, 2023
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Nature had a chat with Dan Weld, Chief Scientist at Semantic Scholar, to discuss how search engines are helping scientists explore and innovate by making it easier to draw connections from a massive collection of scientific literature.

Amanda Heidt