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  2. 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]

  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. 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 ...

  5. Generative artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Generative_artificial...

    Generative AI models are used to power chatbot products such as ChatGPT, programming tools such as GitHub Copilot, [83] text-to-image products such as Midjourney, and text-to-video products such as Runway Gen-2. [84] Generative AI features have been integrated into a variety of existing commercially available products such as Microsoft Office ...

  6. Comparison of reference management software - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_reference...

    Some reference management software include support for automatic embedding and (re)formatting of references in Word processor programs. This table lists this type of support for Microsoft Word , Pages , Apache OpenOffice / LibreOffice Writer , the LaTeX editors Kile and LyX , and Google Docs .

  7. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...

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