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  1. 41

    The Integration Hypothesis of Human Language Evolution and the Nature of Contemporary Languages by Shigeru eMiyagawa, Shigeru eMiyagawa, Shiro eOjima, Robert C. Berwick, Kazuo eOkanoya, Kazuo eOkanoya

    Published 2014-06-01
    “…E and L integrated uniquely in humans to give rise to language. A challenge to the Integration Hypothesis is that while these non-human systems are finite-state in nature, human language is known to require characterization by a non-finite state grammar. …”
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  2. 42

    Large Language Models are Not Models of Natural Language: They are Corpus Models by Csaba Veres

    Published 2022-01-01
    Subjects: “…Natural language processing…”
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  3. 43

    The integration hypothesis of human language evolution and the nature of contemporary languages by Miyagawa, Shigeru, Ojima, Shiro, Berwick, Robert C., Okanoya, Kazuo

    Published 2014
    “…E and L integrated uniquely in humans to give rise to language. A challenge to the Integration Hypothesis is that while these non-human systems are finite-state in nature, human language is known to require characterization by a non-finite state grammar. …”
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  4. 44

    USING A META-LANGUAGE TO BRIDGE THE GAP BETWEEN NATURAL LANGUAGES AND COMPUTER LANGUAGES by Selin Temizer

    Published 2007-07-01
    Subjects: “…Natural language processing…”
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    Introduction to Arabic natural language processing / by 516629 Habash, Nizar Y.

    Published 2010
    Subjects: “…Natural language processing (Computer science)…”
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    Natural language processing : semantic aspects / by Kapetanios, Epaminondas, Tatar, Doina, Sacarea, Christian

    Published 2014
    Subjects: “…Natural language processing (Computer science)…”
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    Natural language generation in interactive systems / by Stent, Amanda, 1974-, editor, Bangalore, Srinivas, 1969-

    Published 2014
    Subjects: “…Natural language processing (Computer science)…”
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    Discovery of Kolmogorov Scaling in the Natural Language by Maurice H. P. M. van Putten

    Published 2017-05-01
    “…We consider the rate R and variance σ 2 of Shannon information in snippets of text based on word frequencies in the natural language. We empirically identify Kolmogorov’s scaling law in σ 2 ∝ k - 1 . 66 ± 0 . 12 (95% c.l.) as a function of k = 1 / N measured by word count N. …”
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