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1
How Efficiency Shapes Human Language
In: https://hal.archives-ouvertes.fr/hal-03552539 ; 2022 (2022)
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2
A verb-frame frequency account of constraints on long-distance dependencies in English
In: Prof. Gibson (2022)
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3
Dependency locality as an explanatory principle for word order
In: Prof. Levy (2022)
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4
When classifying grammatical role, BERT doesn't care about word order... except when it matters ...
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5
Grammatical cues are largely, but not completely, redundant with word meanings in natural language ...
Abstract: The combinatorial power of language has historically been argued to be enabled by syntax: rules that allow words to combine hierarchically to convey complex meanings. But how important are these rules in practice? We performed a broad-coverage cross-linguistic investigation of the importance of grammatical cues for interpretation. First, English and Russian speakers (n=484) were presented with subjects, verbs, and objects (in random order and with morphological markings removed) extracted from naturally occurring sentences, and were asked to identify which noun is the agent of the action. Accuracy was high in both languages (~89% in English, ~87% in Russian), suggesting that word meanings strongly constrain who is doing what to whom. Next, we trained a neural network machine classifier on a similar task: predicting which nominal in a subject-verb-object triad is the subject. Across 30 languages from eight language families, performance was consistently high: a median accuracy of 87%, comparable to the ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.2201.12911
https://arxiv.org/abs/2201.12911
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6
Learning Constraints on Wh-Dependencies by Learning How to Efficiently Represent Wh-Dependencies: A Developmental Modeling Investigation With Fragment Grammars
In: Proceedings of the Society for Computation in Linguistics (2022)
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7
When Classifying Arguments, BERT Doesn't Care About Word Order. Except When It Matters
In: Proceedings of the Society for Computation in Linguistics (2022)
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8
Word order affects the frequency of adjective use across languages
In: Proceedings of the Annual Meeting of the Cognitive Science Society, vol 43, iss 43 (2021)
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9
Syntactic dependencies correspond to word pairs with high mutual information
In: Association for Computational Linguistics (2021)
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10
Hierarchical Representation in Neural Language Models: Suppression and Recovery of Expectations
In: Association for Computational Linguistics (2021)
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11
Structural Supervision Improves Few-Shot Learning and Syntactic Generalization in Neural Language Models
In: Association for Computational Linguistics (2021)
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12
Syntactic dependencies correspond to word pairs with high mutual information
In: Association for Computational Linguistics (2021)
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13
Structural Supervision Improves Learning of Non-Local Grammatical Dependencies
In: Association for Computational Linguistics (2021)
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14
Maze Made Easy: Better and easier measurement of incremental processing difficulty
In: Other repository (2021)
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15
An Information-Theoretic Characterization of Morphological Fusion ...
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16
Deep Subjecthood: Higher-Order Grammatical Features in Multilingual BERT ...
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17
Multilingual BERT, Ergativity, and Grammatical Subjecthood ...
Papadimitriou, Isabel; Chi, Ethan A.; Futrell, Richard. - : University of Massachusetts Amherst, 2021
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18
Sensitivity as a Complexity Measure for Sequence Classification Tasks ...
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19
What do RNN Language Models Learn about Filler–Gap Dependencies?
In: Association for Computational Linguistics (2021)
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20
Language Learning and Processing in People and Machines
In: Association for Computational Linguistics (2021)
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