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  2. Methods of neuro-linguistic programming - Wikipedia

    en.wikipedia.org/wiki/Methods_of_neuro...

    The methods of neuro-linguistic programming are the specific techniques used to perform and teach neuro-linguistic programming, [1] [2] which teaches that people are only able to directly perceive a small part of the world using their conscious awareness, and that this view of the world is filtered by experience, beliefs, values, assumptions, and biological sensory systems.

  3. Neuro-linguistic programming - Wikipedia

    en.wikipedia.org/wiki/Neuro-linguistic_programming

    [k] While some NLP practitioners have argued that the lack of empirical support is due to insufficient research which tests NLP, [l] the consensus scientific opinion is that NLP is pseudoscience [m] [n] and that attempts to dismiss the research findings based on these arguments "[constitute]s an admission that NLP does not have an evidence base ...

  4. Natural-language programming - Wikipedia

    en.wikipedia.org/wiki/Natural-language_programming

    Natural-language programming (NLP) is an ontology-assisted way of programming in terms of natural-language sentences, e.g. English. [1] A structured document with Content, sections and subsections for explanations of sentences forms a NLP document, which is actually a computer program. Natural language programming is not to be mixed up with ...

  5. Natural language processing - Wikipedia

    en.wikipedia.org/wiki/Natural_language_processing

    Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence.It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics.

  6. Question answering - Wikipedia

    en.wikipedia.org/wiki/Question_answering

    The retriever is aimed at retrieving relevant documents related to a given question, while the reader is used to infer the answer from the retrieved documents. Systems such as GPT-3, T5, [8] and BART [9] use an end-to-end [jargon] architecture in which a transformer-based [jargon] architecture stores large-scale textual data in the underlying ...

  7. Information extraction - Wikipedia

    en.wikipedia.org/wiki/Information_extraction

    Information extraction is the part of a greater puzzle which deals with the problem of devising automatic methods for text management, beyond its transmission, storage and display. The discipline of information retrieval (IR) [ 3 ] has developed automatic methods, typically of a statistical flavor, for indexing large document collections and ...

  8. Reinforcement learning from human feedback - Wikipedia

    en.wikipedia.org/wiki/Reinforcement_learning...

    Though RLHF does not require massive amounts of data to improve performance, sourcing high-quality preference data is still an expensive process. Furthermore, if the data is not carefully collected from a representative sample, the resulting model may exhibit unwanted biases. High-level overview of reinforcement learning from human feedback

  9. Automatic summarization - Wikipedia

    en.wikipedia.org/wiki/Automatic_summarization

    In this way, TextRank does not rely on any previous training data at all, but rather can be run on any arbitrary piece of text, and it can produce output simply based on the text's intrinsic properties. Thus the algorithm is easily portable to new domains and languages. TextRank is a general purpose graph-based ranking algorithm for NLP ...

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