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  2. Wordtune - Wikipedia

    en.wikipedia.org/wiki/Wordtune

    Users can use the tool to paraphrase text being composed on services like Gmail, Google Docs, Facebook, Twitter, and LinkedIn. [ 10 ] On November 14, 2021, AI21 released Wordtune Read — an AI-powered Chrome extension and standalone app designed to process large amounts of written text from websites, documents, or YouTube videos, and summarize ...

  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. QuillBot - Wikipedia

    en.wikipedia.org/wiki/QuillBot

    Research from 2021 proposed that QuillBot could potentially be used for paraphrasing tasks, but indicated the importance of English language proficiency for using it properly. [ 7 ] [ 8 ] [ 9 ] See also

  5. Paraphrasing (computational linguistics) - Wikipedia

    en.wikipedia.org/wiki/Paraphrasing...

    The evaluation of paraphrase generation has similar difficulties as the evaluation of machine translation. The quality of a paraphrase depends on its context, whether it is being used as a summary, and how it is generated, among other factors. Additionally, a good paraphrase usually is lexically dissimilar from its source phrase.

  6. Perplexity AI - Wikipedia

    en.wikipedia.org/wiki/Perplexity_AI

    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 ] [ 4 ] Its developer, Perplexity AI, Inc., is based in San Francisco, California .

  7. GPT-2 - Wikipedia

    en.wikipedia.org/wiki/GPT-2

    GPT-2 became capable of performing a variety of tasks beyond simple text production due to the breadth of its dataset and technique: answering questions, summarizing, and even translating between languages in a variety of specific domains, without being instructed in anything beyond how to predict the next word in a sequence.