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One model for the learning of language.
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In: Proceedings of the National Academy of Sciences of the United States of America, vol 119, iss 5 (2022)
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Abstract:
A major goal of linguistics and cognitive science is to understand what class of learning systems can acquire natural language. Until recently, the computational requirements of language have been used to argue that learning is impossible without a highly constrained hypothesis space. Here, we describe a learning system that is maximally unconstrained, operating over the space of all computations, and is able to acquire many of the key structures present in natural language from positive evidence alone. We demonstrate this by providing the same learning model with data from 74 distinct formal languages which have been argued to capture key features of language, have been studied in experimental work, or come from an interesting complexity class. The model is able to successfully induce the latent system generating the observed strings from small amounts of evidence in almost all cases, including for regular (e.g., an , [Formula: see text], and [Formula: see text]), context-free (e.g., [Formula: see text], and [Formula: see text]), and context-sensitive (e.g., [Formula: see text], and xx) languages, as well as for many languages studied in learning experiments. These results show that relatively small amounts of positive evidence can support learning of rich classes of generative computations over structures. The model provides an idealized learning setup upon which additional cognitive constraints and biases can be formalized.
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Keyword:
computational linguistics; formal language theory; Humans; Language; Learning; learning theory; Linguistics; program induction
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URL: https://escholarship.org/uc/item/6sb6g4gx
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One model for the learning of language
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In: Proc Natl Acad Sci U S A (2022)
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Developing an Automatic System for Classifying Chatter About Health Services on Twitter: Case Study for Medicaid
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In: J Med Internet Res (2021)
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Self-reported COVID-19 symptoms on Twitter: an analysis and a research resource
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In: J Am Med Inform Assoc (2020)
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A Light-Weight Text Summarization System for Fast Access to Medical Evidence
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In: Front Digit Health (2020)
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Entwicklung interkultureller Handlungskompetenz : ein didaktisches Konzept für den Wirtschaftsdeutschunterricht in China am Beispiel des Einsatzes von Lernvideos
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Yang, Yuan [Verfasser]. - München : Iudicium, 2019
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DNB Subject Category Language
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Entwicklung interkultureller Handlungskompetenz. Ein didaktisches Konzept für den Wirtschaftsdeutschunterricht in China am Beispiel des Einsatzes von Lernvideos
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DNB Subject Category Language
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Punctuation and Parallel Corpus Based Word Embedding Model for Low-Resource Languages
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In: Information ; Volume 11 ; Issue 1 (2019)
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