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Language, Brains & Interpretability ...
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Syntactic Persistence in Language Models: Priming as a Window into Abstract Language Representations ...
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3
Artificial Grammar Learning in children, adults, animals and machines
In: ISSN: 1756-8757 ; EISSN: 1756-8765 ; Topics in cognitive science ; https://hal.archives-ouvertes.fr/hal-02877137 ; Topics in cognitive science, Wiley, 2020 (2020)
Abstract: International audience ; Human languages all have a grammar, i.e. rules that determine how symbols in a language can be combined to create complex meaningful expressions. Despite decades of research, the evolutionary, developmental, cognitive and computational bases of grammatical abilities are still not fully understood. "Artificial Grammar Learning" (AGL) studies provide important insights into how rules and structured sequences are learned, the relevance of these processes to language in humans and the evolutionarily conserved cognitive systems that may be shared with other animals. AGL tasks can be used to study how human adults, infants, animals or machines learn artificial grammars of various sorts, consisting of rules defined typically over syllables, sounds or visual items. In this introduction, we distill some lessons from the nine others papers in this special issue, which review the advances made from this growing body of literature. We provide a critical synthesis, identify the questions that remain open, and recognize the challenges that lie ahead. A key observation across the disciplines is that the limits of human, animal and machine capabilities have yet to be reached. Thus, this interdisciplinary area of research firmly rooted in the cognitive sciences has unearthed exciting new questions and venues for research, along the way fostering impactful collaborations between traditionally disconnected disciplines that are breaking scientific ground.
Keyword: [SCCO]Cognitive science
URL: https://hal.archives-ouvertes.fr/hal-02877137
https://hal.archives-ouvertes.fr/hal-02877137/document
https://hal.archives-ouvertes.fr/hal-02877137/file/topiCS-preprint.pdf
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4
DoLFIn: Distributions over Latent Features for Interpretability ...
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5
Mode classification and natural units in plainchant ...
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6
Mode classification and natural units in plainchant ...
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7
Blackbox meets blackbox: Representational Similarity and Stability Analysis of Neural Language Models and Brains ...
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8
Formal models of structure building in music, language, and animal song
In: The origins of musicality (Cambridge, 2018), p. 253-286
MPI für Psycholinguistik
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9
Five fundamental constraints on theories of the origins of music
In: The origins of musicality (Cambridge, 2018), p. 49-80
MPI für Psycholinguistik
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10
Under the Hood: Using Diagnostic Classifiers to Investigate and Improve how Language Models Track Agreement Information ...
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11
Experiential, Distributional and Dependency-based Word Embeddings have Complementary Roles in Decoding Brain Activity ...
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12
Analyzing the Structure of Bird Vocalizations and Language: Finding Common Ground
In: Birdsong, speech, and language : exploring the evolution of mind and brain (2016), S. 243-260
Leibniz-Zentrum Allgemeine Sprachwissenschaft
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13
Analyzing the structure of bird vocalizations and language : finding common ground
In: Birdsong, speech and language (Cambridge, 2013), p. 243-260
MPI für Psycholinguistik
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14
Modeling in the language sciences
In: Research methods in linguistics (Cambridge, 2013), p. 422-439
MPI für Psycholinguistik
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15
Analyzing the structure of bird vocalizations and language : finding common ground
In: Birdsong, speech and language (Cambridge, 2013), p. 243-260
MPI für Psycholinguistik
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16
Three design principles of language: the search for parsimony in redundancy
In: Language and speech. - London [u.a.] : Sage Publ. 56 (2013) 3, 265-290
BLLDB
OLC Linguistik
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17
What are the unique design features of language? Formal tools for comparative claims
In: Adaptive behavior. - Thousand Oaks, Calif. : Sage 18 (2010) 1, 48-65
BLLDB
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18
The evolution of combinatorial phonology
In: Journal of phonetics. - Amsterdam : Elsevier 37 (2009) 2, 125-144
BLLDB
OLC Linguistik
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19
Children's grammars grow more abstract with age - evidence from an automatic procedure for identifying the productive units of language
In: Topics in cognitive science. - Hoboken, NJ [u.a.] : Wiley 1 (2009) 1, 175-188
BLLDB
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20
Children's Grammars Grow More Abstract with Age — Evidence from an Automatic Procedure for Identifying the Productive Units of Language
In: Topics in cognitive science. - Hoboken, NJ [u.a.] : Wiley 1 (2009) 1, 175-188
OLC Linguistik
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