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  2. TL;DR: This AI summarizes research papers so you don ... - AOL

    www.aol.com/tl-dr-ai-summarizes-research...

    Reading scientific papers is a tough job. Thankfully, researchers at the Allen Institute for Artificial Intelligence have developed a new model to summarize text from scientific papers, and ...

  3. Automatic summarization - Wikipedia

    en.wikipedia.org/wiki/Automatic_summarization

    Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.

  4. Semantic Scholar - Wikipedia

    en.wikipedia.org/wiki/Semantic_Scholar

    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]

  5. GPT-2 - Wikipedia

    en.wikipedia.org/wiki/GPT-2

    GPT-2's flexibility was described as "impressive" by The Verge; specifically, its ability to translate text between languages, summarize long articles, and answer trivia questions were noted. [ 17 ] A study by the University of Amsterdam employing a modified Turing test found that at least in some scenarios, participants were unable to ...

  6. NotebookLM - Wikipedia

    en.wikipedia.org/wiki/NotebookLM

    An example of an AI-generated conversation by NotebookLM (January 2025) NotebookLM (Google NotebookLM) is a research and note-taking online tool developed by Google Labs that uses artificial intelligence (AI), specifically Google Gemini , to assist users in interacting with their documents.

  7. Generative pre-trained transformer - Wikipedia

    en.wikipedia.org/wiki/Generative_pre-trained...

    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.

  8. Executive summary - Wikipedia

    en.wikipedia.org/wiki/Executive_summary

    Executive summaries are important as a communication tool in both academia and business. For example, members of Texas A&M University's Department of Agricultural Economics observe that "An executive summary is an initial interaction between the writers of the report and their target readers: decision makers, potential customers, and/or peers.

  9. Multi-document summarization - Wikipedia

    en.wikipedia.org/wiki/Multi-document_summarization

    Multi-document summarization is an automatic procedure aimed at extraction of information from multiple texts written about the same topic. The resulting summary report allows individual users, such as professional information consumers, to quickly familiarize themselves with information contained in a large cluster of documents.

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