Semantic Scholar

Semantic Scholar is an AI-powered research tool that helps scholars discover and understand scientific literature. It provides comprehensive and contextual insights into a vast corpus of academic papers, leveraging advanced artificial intelligence to enhance the research process.

Key features:
- AI-Powered Search: Uses semantic understanding to provide relevant results across nearly 200 million academic papers.
- Field of Study Selection: Allows filtering of search results by specific academic domains.
- Date Range and Publication Filters: Enables refinement of results by date, publication type, authors, journals, and conferences.
- Scientific Literature Graph: Offers a comprehensive graph of billions of citations for navigating influential research.
- Citation Classifications: Categorizes citations as 'Cites Results', 'Cites Methods', or 'Cites Background' for better context understanding.
- Highly Influential Citations: Identifies and highlights important citations within the literature.
- Key Information Extraction: Presents essential information from papers, including figures, tables, topics, and references.
- Multimedia Integration: Includes related videos, presentations, code libraries, and clinical trials.
- News and Blog Articles: Provides access to news or blog articles discussing the paper.
- Semantic Reader: Offers an augmented reading experience for enhanced accessibility and contextual understanding of scientific papers (in beta for select papers).

How it works:
1. Users access the web application and enter natural language queries.
2. The AI-powered search engine processes the query, understanding its context and semantics.
3. Results are displayed, which can be filtered by various criteria such as field of study, date range, or publication type.
4. Users can explore detailed paper pages that aggregate key information and multimedia content.
5. The platform's AI capabilities provide contextually relevant results and insights throughout the process.

Integrations:
Paper Search API for developers to build scholarly applications

Use of AI:
Semantic Scholar uses advanced natural language processing models to understand the semantics of scientific literature and provide contextually relevant search results. These AI capabilities enhance the search experience and citation analysis features.

AI foundation model:
The platform's AI models are built on state-of-the-art research conducted by the Allen Institute for AI, focusing on natural language processing for scientific literature.

Target users:
- Academic researchers and scholars across various fields of study
- Students and educators seeking reliable and comprehensive academic resources
- Developers building scholarly applications requiring advanced search and citation analysis capabilities

How to access:
Semantic Scholar is available as a free web application. It also offers an API for developers to integrate its capabilities into other scholarly applications.