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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 Hits 1 – 20 of 27 1 One model for the learning of language. Yang, Yuan; Piantadosi, Steven T In: Proceedings of the National Academy of Sciences of the United States of America, vol 119, iss 5 (2022) BASE Show details 2 One model for the learning of language Yang, Yuan; Piantadosi, Steven T. In: Proc Natl Acad Sci U S A (2022) BASE Show details 3 The Child as Hacker Rule, Joshua S; Tenenbaum, Joshua B; Piantadosi, Steven T In: PMC (2021) BASE Show details 4 The Natural Stories corpus: a reading-time corpus of English texts containing rare syntactic constructions [<Journal>] Futrell, Richard [Verfasser]; Gibson, Edward [Verfasser]; Blank, Idan [Verfasser]. DNB Subject Category Language Show details 5 The Natural Stories corpus: a reading-time corpus of English texts containing rare syntactic constructions Futrell, Richard; Gibson, Edward A; Tily, Harry J.... In: Springer Netherlands (2020) BASE Show details 6 Recursive sequence generation in monkeys, children, U.S. adults, and native Amazonians Ferrigno, Stephen; Cheyette, Samuel J.; Piantadosi, Steven T.... In: Sci Adv (2020) BASE Show details 7 Post Hoc Analysis Decisions Drive the Reported Reading Time Effects in Hackl, Koster-Hale & Varvoutis (2012) Gibson, Edward; Piantadosi, Steven T; Levy, Roger In: Other repository (2019) BASE Show details 8 Table of assumptions used in our estimates from Humans store about 1.5 megabytes of information during language acquisition ... Mollica, Francis; Piantadosi, Steven T.. - : The Royal Society, 2019 BASE Show details 9 Table of assumptions used in our estimates from Humans store about 1.5 megabytes of information during language acquisition ... Mollica, Francis; Piantadosi, Steven T.. - : The Royal Society, 2019 BASE Show details 10 Supplementary material from "Humans store about 1.5 megabytes of information during language acquisition" ... Mollica, Francis; Piantadosi, Steven T.. - : Figshare, 2019 BASE Show details 11 Supplementary material from "Humans store about 1.5 megabytes of information during language acquisition" ... Mollica, Francis; Piantadosi, Steven T.. - : Figshare, 2019 BASE Show details 12 One-to-one correspondence without language Koopman, Sarah E.; Arre, Alyssa M.; Piantadosi, Steven T.. - : The Royal Society, 2019 BASE Show details 13 Word Forms Are Structured for Efficient Use Mahowald, Kyle Adam; Dautriche, Isabelle; Gibson, Edward A... In: Prof. Gibson via Courtney Crummett (2018) BASE Show details 14 Color naming across languages reflects color use Ratnasingam, Sivalogeswaran; Piantadosi, Steven T.; Conway, Bevil R.... In: National Academy of Sciences (2018) BASE Show details 15 Words cluster phonetically beyond phonotactic regularities Dautriche, Isabelle; Christophe, Anne; Piantadosi, Steven T.... In: Prof. Gibson via Courtney Crummett (2017) BASE Show details 16 The Natural Stories Corpus ... Futrell, Richard; Gibson, Edward; Tily, Hal. - : arXiv, 2017 BASE Show details 17 Color naming across languages reflects color use Gibson, Edward; Futrell, Richard; Jara-Ettinger, Julian; Mahowald, Kyle; Bergen, Leon; Ratnasingam, Sivalogeswaran; Gibson, Mitchell; Piantadosi, Steven T.; Conway, Bevil R.. - : National Academy of Sciences, 2017 Abstract: The number of color terms varies drastically across languages. Yet despite these differences, certain terms (e.g., red) are prevalent, which has been attributed to perceptual salience. This work provides evidence for an alternative hypothesis: The use of color terms depends on communicative needs. Across languages, from the hunter-gatherer Tsimane' people of the Amazon to students in Boston, warm colors are communicated more efficiently than cool colors. This cross-linguistic pattern reflects the color statistics of the world: Objects (what we talk about) are typically warm-colored, and backgrounds are cool-colored. Communicative needs also explain why the number of color terms varies across languages: Cultures vary in how useful color is. Industrialization, which creates objects distinguishable solely based on color, increases color usefulness. Keyword: Biological Sciences URL: http://www.ncbi.nlm.nih.gov/pubmed/28923921 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5635863/ https://doi.org/10.1073/pnas.1619666114 BASE Hide details 18 Wordform Similarity Increases With Semantic Similarity: An Analysis of 100 Languages Dautriche, Isabelle; Piantadosi, Steven T.; Mahowald, Kyle Adam... In: Prof. Gibson via Courtney Crummett (2016) BASE Show details 19 A Corpus Investigation of Syntactic Embedding in Pirahã Futrell, Richard; Stearns, Laura; Everett, Daniel L.. - : Public Library of Science, 2016 BASE Show details 20 A Corpus Investigation of Syntactic Embedding in Piraha Stearns, Laura; Everett, Daniel L.; Piantadosi, Steven T.... In: PLoS (2015) BASE Show details Page: 1 2

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