About Semantic Scholar

Helping Scholars Discover New Insights

Semantic Scholar provides free, AI-driven search and discovery tools, and open resources for the global research community.

We index over 200 million academic papers sourced from publisher partnerships, data providers, and web crawls.

Illustration: Papers being accelerated by Semantic Scholar

Our Mission

Accelerating Scientific Breakthroughs Using AI

We are a Research and Product Development team within the Allen Institute for AI building a better way to search and discover scientific knowledge.

Developed in-house, our state-of-the-art models process and classify papers in our pipeline. We distribute open code and datasets while publishing results of our research in the areas of Natural Language Processing, Machine Learning, Human Computer Interaction, and Information Retrieval.

AI-Driven Tools for Scholars

Staying up-to-date with scientific literature is an increasingly pressing challenge for scholars.

With Semantic Scholar, researchers can understand a paper at a glance. Our system extracts meaning and identifies connections from within papers, then surfaces these insights to help Scholars discover and understand research.

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Our Values

Our Values reflect who we are, why we are building Semantic Scholar, and guide us through hard decisions.

Apply AI Creatively

We are motivated to use AI in novel ways for a dramatic impact. Tackling our problems with AI not only helps our community, it also improves the quality of our AI research by grounding it in real-world application.

Promote Equal Access to Science

Scientific knowledge should be available to everyone. We recognize that the status quo disproportionately benefits certain groups of scholars over others. As a non-profit, we evaluate the impact of our choices and pursue directions that help balance the scales.

Be Collaborative

Collaboration makes us stronger. We make a conscious effort to collaborate with our teammates, and by doing so, we will both improve the quality of our work and distribute the burden of support.

Take Bold Measures

We are small, but mighty. We stand behind our convictions when we believe they are the right direction, even if that is a more difficult path. We question what has been done historically, never satisfied with the status quo.

Learn Early

We aim to gain knowledge sooner by starting conversations early and by prototyping our ideas quickly. When we realize a path we have chosen is not working, we are willing to recognize it openly and do the work to learn from it.

Be Trustworthy and Transparent

We aim to establish a higher standard for applying AI in a trustworthy and transparent way. By educating and building trust in our AI-driven solutions, we will foster a community who are invested in our success and patient with our mistakes.

Resources for the Global Research Community

We provide a free, reliable source of scholarly data for developers to build projects that accelerate scientific progress.

The Semantic Scholar Academic Graph (S2AG) Dataset and APIs provide records for research papers published in all fields provided as an easy-to-use JSON archive. The Semantic Scholar Open Research Corpus (S2ORC) is a general purpose corpus for NLP and text mining research over scientific papers built and maintained by Semantic Scholar’s research team. Papers are aggregated into a unified source to create the largest publicly-available collection of machine-readable academic text, provided as a JSON archive.

AI For The Common Good

At AI2, our mission is to contribute to humanity through high-impact AI research and engineering.

Semantic Scholar was launched in 2015 as a groundbreaking project at the Allen Institute for AI, a non-profit research institute founded in 2014 with the mission of conducting high-impact AI research and engineering in service of the common good. AI2 is the creation of Paul Allen, Microsoft co-founder, and is led by Dr. Oren Etzioni, a leading AI researcher.

Are you interested in our mission? Join the team!

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Latest News & Updates

Case Study: Iterative Design for Skimming Support

Case Study: Iterative Design for Skimming Support

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.

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

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

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.

Artificial-intelligence search engines wrangle academic literature

Artificial-intelligence search engines wrangle academic literature

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.