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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.
The project uses a combination of machine learning, natural language processing, and machine vision to add a layer of semantic analysis to the traditional methods of citation analysis, and to extract relevant figures, tables, entities, and venues from papers. [9] [10] Another key AI-powered feature is Research Feeds, an adaptive research ...
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Perplexity AI is a conversational search engine that uses large language models (LLMs) to answer queries using sources from the web and cites links within the text response. [3] Its developer, Perplexity AI, Inc., is based in San Francisco, California .
A paper generator is computer software that composes scholarly papers in the style of those that appear in academic journals or conference proceedings. Typically, the generator uses technical jargon from the field to compose sentences that are grammatically correct and seem erudite but are actually nonsensical. [ 1 ]
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