Can AI solve the crisis of unread scientific literature?
In short: Every year, three million new scientific papers are published, but it is estimated that only half of them ever get read. Semantic Scholar aims to bridge this gap by using artificial intelligence to distill complex research into digestible summaries and hidden connections.
Developed at the Allen Institute for AI and released in 2015, Semantic Scholar is a research tool designed to navigate the overwhelming volume of modern science. By September 2022, its corpus expanded to include over 200 million publications across all fields. Unlike traditional search engines like Google Scholar or PubMed, it focuses on highlighting influential elements and identifying hidden links between topics using graph structures such as the Microsoft Academic Knowledge Graph.
The platform employs "abstractive" techniques—a combination of machine learning, natural language processing (NLP), and machine vision—to capture the essence of papers. This allows for the generation of one-sentence summaries and TLDRs (Too Long; Didn't Read) within its Semantic Reader. These features are specifically designed to help researchers digest information faster on mobile devices where reading lengthy abstracts is difficult.
Beyond simple search, the tool offers Research Feeds, an adaptive recommender that uses a paper embedding model trained via contrastive learning to suggest new content based on a user's specific interests. It also serves as a foundational infrastructure; its corpus provides the primary data for many emerging AI discovery tools like Elicit and SciSpace.
While it offers sophisticated semantic analysis, there are notable limitations. For instance, while the Semantic Reader allows users to ask an AI Assistant questions about methodology or sample sizes when a PDF is available, the general search results do not automatically extract data or provide summaries for every result.
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Sources
- Summary by Intellect · source: Semantic Scholar
- Also: Frontiers in research metrics and analytics — Artificial intelligence research in school leadership and management: a text mining-based computational literature review and future directions. · CC BY
- Also: libguides.northampton.ac.uk — Semantic Scholar - AI Tools for Research - Library at University of Northampton
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