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For example, the set cover problem is a special case of submodular optimization, since the set cover function is submodular. The set cover function attempts to find a subset of objects which cover a given set of concepts. For example, in document summarization, one would like the summary to cover all important and relevant concepts in the document.
Semantic Scholar is a research tool for scientific literature. It is developed at the Allen Institute for AI and was publicly released in November 2015. [2] Semantic Scholar uses modern techniques in natural language processing to support the research process, for example by providing automatically generated summaries of scholarly papers. [3]
Thankfully, researchers at the Allen Institute for Artificial Intelligence have developed a new model to summarize text from scientific papers, and present it in a few sentences in the form of TL ...
Generative artificial intelligence (generative AI, GenAI, [165] or GAI) is a subset of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data. [ 166 ] [ 167 ] [ 168 ] These models learn the underlying patterns and structures of their training data and use them to produce new data [ 169 ...
APA style (also known as APA format) is a writing style and format for academic documents such as scholarly journal articles and books. It is commonly used for citing sources within the field of behavioral and social sciences , including sociology, education, nursing, criminal justice, anthropology, and psychology.
An executive summary (or management summary, sometimes also called speed read) is a short document or section of a document produced for business purposes. It summarizes a longer report or proposal or a group of related reports in such a way that readers can rapidly become acquainted with a large body of material without having to read it all.
Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.
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related to: ai that summarizes long articles apa 7 version pdf example free