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  2. 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 .

  3. Information extraction - Wikipedia

    en.wikipedia.org/wiki/Information_extraction

    Recent effort on adaptive information extraction motivates the development of IE systems that can handle different types of text, from well-structured to almost free text -where common wrappers fail- including mixed types. Such systems can exploit shallow natural language knowledge and thus can be also applied to less structured texts.

  4. Artificial intelligence content detection - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence...

    Multiple AI detection tools have been demonstrated to be unreliable in terms of accurately and comprehensively detecting AI-generated text. In a study conducted by Weber-Wulff et al., and published in 2023, researchers evaluated 14 detection tools including Turnitin and GPT Zero, and found that "all scored below 80% of accuracy and only 5 over 70%."

  5. List of academic databases and search engines - Wikipedia

    en.wikipedia.org/wiki/List_of_academic_databases...

    The main academic full-text databases are open archives or link-resolution services, although others operate under different models such as mirroring or hybrid publishers. Such services typically provide access to full text and full-text search, but also metadata about items for which no full text is available.

  6. Semantic Scholar - Wikipedia

    en.wikipedia.org/wiki/Semantic_Scholar

    The AI technology is designed to identify hidden connections and links between research topics. [14] Like the previously cited search engines, Semantic Scholar also exploits graph structures, which include the Microsoft Academic Knowledge Graph , Springer Nature's SciGraph , and the Semantic Scholar Corpus (originally a 45 million papers corpus ...

  7. Knowledge extraction - Wikipedia

    en.wikipedia.org/wiki/Knowledge_extraction

    Knowledge extraction is the creation of knowledge from structured (relational databases, XML) and unstructured (text, documents, images) sources.The resulting knowledge needs to be in a machine-readable and machine-interpretable format and must represent knowledge in a manner that facilitates inferencing.

  8. Wikipedia:List of free online resources - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:List_of_free...

    The following list is meant to help you with your own research, by offering links to respectable information sources on the web, available free of charge. Inclusion on the list doesn't automatically mean the absolute truth is on these websites, so always be critical and compare information between different sources.

  9. T5 (language model) - Wikipedia

    en.wikipedia.org/wiki/T5_(language_model)

    T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [ 1 ] [ 2 ] Like the original Transformer model, [ 3 ] T5 models are encoder-decoder Transformers , where the encoder processes the input text, and the decoder generates the output text.

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