Results 11 to 20 of about 17,696,681 (275)

Language change for the worse [PDF]

Many theories hold that language change, at least on a local level, is driven by a need for improvement. The present volume explores to what extent this assumption holds true, and whether there is a particular type of language change that we dub language
Schaden, Gerhard, Hyman, Larry M.; University of California, Berkeley, Elsweiler, Christine, Hölzl, Andreas, Faytak, Matthew, Hölzl, Andreas; University of Potsdam, Lapierre, Myriam, Weber, Thilo; Leibniz Institute for the German Language, Seiler, Guido; University of Zurich, Matoshi, Veton, Enke, Dankmar W.; LMU Munich, Nichols, Johanna; University of California, Berkeley, Deo, Ashwini, Huber, Judith, Reiner, Tabea, Jäger, Gerhard, Mühlenbernd, Roland   +16 more
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Natural causes of language: Frames, biases, and cultural transmission [PDF]

, 2014
What causes a language to be the way it is? Some features are universal, some are inherited, others are borrowed, and yet others are internally innovated.
Enfield, N.J.; University of Sydney
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Third language acquisition: Age, proficiency and multilingualism [PDF]

, 2020
This book deals with the phenomenon of third language (L3) acquisition. As a research field, L3 acquisition is established as a branch of multilingualism that is concerned with how multilinguals learn additional languages and the role that their ...
Gudmundson, Anna, Sleeman, Petra, Sánchez, Laura, Sciutti, Sandro, Bardel, Camilla, Salaberry, Rafael, Muñoz, Carmen, Stadt, Rosalinde, Pfenninger, Simone E., Hulk, Aafke   +9 more
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Grammatical systems without language borders: Lessons from free-range language

, 2023
Current research in grammatical analysis and sociolinguistics points to two core characteristics of language that seem incommensurable at first sight: (1) research on linguistic structure indicates internal organisation and coherence, and the workings ...
Wiese, Heike
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Red Teaming Language Models with Language Models

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022
Language Models (LMs) often cannot be deployed because of their potential to harm users in hard-to-predict ways. Prior work identifies harmful behaviors before deployment by using human annotators to hand-write test cases. However, human annotation is expensive, limiting the number and diversity of test cases.
Ethan Perez, Saffron Huang, H. Francis Song, Trevor Cai, Roman Ring, John Aslanides, Amelia Glaese, Nat McAleese, Geoffrey Irving   +8 more
openaire   +4 more sources

Interpreting language-learning data [PDF]

, 2020
This book provides a forum for methodological discussions emanating from researchers engaged in studying how individuals acquire an additional language.
Gudmestad, Aarnes; Virginia Polytechnic Institute and State University, Huang, Xiaoliang; Beijing Foreign Studies University, Leclercq, Pascale; Université Paul Valéry Montpellier 3, Trévisiol, Pascale; Université Paris 3 & DILTEC EA 2288, Watorek, Marzena; Université Paris 8 & UMR-SFL, CNRS, Scheuer, Sylwia; University of Paris 3 – Sorbonne Nouvelle, Horgues, Céline; University of Paris 3 – Sorbonne Nouvelle, Majdoub, Hedi; Université Paris 8 & UMR-SFL, CNRS, Yu, Xinyue Cécilia; Inalco - CNRS - EHESS, CRLAO, Pélissier, Maud; University of Agder, Rast, Rebekah; American University of Paris & UMR-SFL, CNRS, Søfteland, Åshild; Østfold University College, Guan, Qianwen; City University of Hong Kong, Emilsen, Linda Evenstad; Østfold University College, Hilton, Heather E.; Université Lumière Lyon 2, Edmonds, Amanda, Leclercq, Pascale, Osborne, John; Université Savoie Mont Blanc, Gudmestad, Aarnes   +18 more
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A Precis of Language Models are not Models of Language

CoRR, 2022
Natural Language Processing is one of the leading application areas in the current resurgence of Artificial Intelligence, spearheaded by Artificial Neural Networks. We show that despite their many successes at performing linguistic tasks, Large Neural Language Models are ill-suited as comprehensive models of natural language.
openaire   +3 more sources

Language Models are not Models of Language.

CoRR, 2021
Natural Language Processing (NLP) has become one of the leading application areas in the current Artificial Intelligence boom. Transfer learning has enabled large deep learning neural networks trained on the language modeling task to vastly improve performance in almost all downstream language tasks.
openaire   +7 more sources

Paraphrastic language models [PDF]

Interspeech 2012, 2012
Natural languages are known for their expressive richness. Many sentences can be used to represent the same underlying meaning. Only modelling the observed surface word sequence can result in poor context coverage and generalization, for example, when using n-gram language models (LMs).
Liu, X, Gales, MJF, Woodland, PC
openaire   +3 more sources

Igbo-English intrasentential codeswitching and the Matrix Language Frame model [PDF]

, 2015
This paper uses data from Igbo-English intrasentential codeswitching involving mixed nominal expressions to test the Matrix Language Frame (MLF) model.
Fagundes Camargos, Quesler; Federal University of Rondônia, Nicolle, Steve; Canada Institute of Linguistics / SIL, Muaka, Leonard; Winston Salem State University, North Carolina, Kawasha, Boniface; Savannah State University, Jerro, Kyle; University of Texas at Austin, Anderson, Gregory D.S.; Living Tongues Institute for Endangered Languages & University of South Africa (UNISA), van der Wal, Jenneke; University of Cambridge, Ngonyani, Deo; Michigan State University, Bowler, Margit; UCLA, Ahland, Michael; California State University, Long Beach, Kari, Ethelbert E.; University of Botswana / University of Port Harcourt, Michieka, Martha; East Tennessee State University, McPherson, Laura; Dartmouth College, Namyalo, Saudah; Makerere University, Korsah, Sampson; Universität Leipzig, Aly, Ann M.; University of California, Los Angeles, Glewwe, Eleanor; University of California, Los Angeles, Pacchiarotti, Sara; University of Oregon, Bosire, Mokaya; University of Oregon, Sibanda, Galen; Michigan State University, Bonfim Duarte, Fábio; Federal University of Minas Gerais, Landman, Meredith; Pomona College, Ihemere, Kelechukwu; University of Westminster, Rolle, Nicholas; University of California, Berkeley, Osam, E. Kweku; University of Ghana, Sarvasy, Hannah; Australian National University, Ihemere, K., Teo, Amos; University of Oregon, Burkholder, Ross; University of Chicago, Gluckmann, John; UCLA, Nilsson, Morgan; University of Gothenburg, Ngowa, Nancy Jumwa; Pwani University, Cahill, Michael; SIL, Safir, Ken; Rutgers, Payne, Doris L.; University of Oregon, Schwarz, Anne; Universidad Regional Amazónica IKIAM, Ahland, Colleen; SIL, Selvanathan, Naga; Rutgers, Atelela Ngunga, Armindoo Saúl; University of Eduardo Mondlane, Moodie, Jonathan; University of Melbourne   +39 more
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