Semantic Scholar: An AI Tool Meant to Assist Individuals with Research

What is Semantic Scholar?

Semantic Scholar is an AI-powered research tool for scientific literature. With billions of citations, Semantic Scholar provides a citation graph that allows scholars to navigate and discover the most relevant research across all fields of study.

How can I use Semantic Scholar?

Semantic Scholar has many uses, including:

• Finding relevant research: Semantic Scholar's AI helps researchers find the most relevant research for their work by identifying connections and extracting meaning from papers.
• Understanding papers quickly: Semantic Scholar helps researchers understand papers at a glance by highlighting important and influential elements.
• Defining words and acronyms: Semantic Scholar's Semantic Reader feature allows researchers to click on any term with a dotted underline to get an AI-generated definition.
• Exploring scientific publication data: Semantic Scholar's REST API allows researchers to find and explore scientific publication data about authors, papers, citations, and venues.

Watch the following video to learn more about the uses and applications of Semantic Scholar:

Why should I take care when using Semantic Scholar?

While generative AI tools like Semantic Scholar can help users with such tasks as locating research articles, organizing existing information, mapping out scholarly discussions, or summarizing sources, the outputs they provide are not always entirely factual or grounded in the best research strategies. To the contrary, Semantic Scholar has been known to hallucinate, or "describe false information created by the AI system to defend its statements." Oftentimes, Semantic Scholar will generate outputs without qualifying the accuracy of the information it provides, and it has been known to confidently provide responses to queries that nonetheless consist of partially or fully fabricated citations or facts.

Additionally, generative AI tools like Semantic Scholar sometimes will provide outputs that lack currency, as some of the large language models that they are trained on lack access to the latest research in a given field of study. In some instances, the information that Semantic Scholar will consult to provide a summary of extant research will be based on old datasets, thereby causing it to frame the information it shares as current when, in reality, it is not.

The use of generative AI tools like Semantic Scholar in academia has also raised many concerns about academic integrity and the respect of intellectual property. One area of academic integrity affected by generative AI tools like Semantic Scholar is that of false citations.

Providing false citations in research, whether one intends to or not, is a violation of St. Catherine University's academic integrity policy. Generative AI tools such as Semantic Scholar have been known to generate false citations, and even if the citations are based on actual papers, the cited content in Semantic Scholar might still be inaccurate, placing the onus of interrogating the accuracy of it on the user of the AI tool.

Where can I find more information about Semantic Scholar?

For more information on Semantic Scholar, please refer to the FAQ page for the generative AI tool.

Last updated December 4, 2024

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