Semantic Scholar uses groundbreaking AI and engineering to understand the semantics of scientific literature to help Scholars discover relevant research.

Semantic Reader Project is a collaborative effort of NLP + HCI researchers from non-profit, industry, and academic institutions to create interactive, intelligent reading interfaces for scholarly papers.

What is the advantage of using Semantic Scholar instead of other academic search engines? Does Semantic Scholar offer programmatic access to its data through an API or downloadable dataset?

To create a better reading experience, Semantic Reader uses artificial intelligence to understand a document’s structure and merge it with the Semantic Scholar’s academic corpus, providing detailed …

Not only is the Semantic Scholar API very easy to use, quick, and reliable, but it also incorporates a lot of additional metadata like PDF URLs, abstract, summarization, and more, that are not easily …

The Semantic Scholar REST API uses standard HTTP verbs, response codes, and authentication. This tutorial will teach you how to interact with the API by sending requests and analyzing the responses.

The new TLDR feature in Semantic Scholar automatically generates single-sentence paper summaries using GPT-3 style techniques, helping you decide which papers to read.

Examples: https://api.semanticscholar.org/graph/v1/paper/search/match?query=Construction of the Literature Graph in Semantic Scholar Returns a single paper that is the closest title match. Each …

Semantic Scholar extracted view of "Language, culture, and translating" by E. Nida

This paper aims to link syntactic and semantic representations in simple sentences and the structure of complex sentences by linking syntax and semantics in complex sentences.