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Dependency locality as an explanatory principle for word order
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In: Prof. Levy (2022)
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A Systematic Assessment of Syntactic Generalization in Neural Language Models
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In: Association for Computational Linguistics (2021)
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Hierarchical Representation in Neural Language Models: Suppression and Recovery of Expectations
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In: Association for Computational Linguistics (2021)
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Abstract:
Work using artificial languages as training input has shown that LSTMs are capable of inducing the stack-like data structures required to represent context-free and certain mildly context-sensitive languages — formal language classes which correspond in theory to the hierarchical structures of natural language. Here we present a suite of experiments probing whether neural language models trained on linguistic data induce these stack-like data structures and deploy them while incrementally predicting words. We study two natural language phenomena: center embedding sentences and syntactic island constraints on the filler–gap dependency. In order to properly predict words in these structures, a model must be able to temporarily suppress certain expectations and then recover those expectations later, essentially pushing and popping these expectations on a stack. Our results provide evidence that models can successfully suppress and recover expectations in many cases, but do not fully recover their previous grammatical state.
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URL: https://hdl.handle.net/1721.1/130418
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Cognitive Science Honors the Memory of Jeffrey Elman
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In: MIT Press (2021)
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SyntaxGym: An Online Platform for Targeted Evaluation of Language Models
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In: Association for Computational Linguistics (2021)
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Neural language models as psycholinguistic subjects: Representations of syntactic state
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In: Association for Computational Linguistics (2021)
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Structural Supervision Improves Learning of Non-Local Grammatical Dependencies
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In: Association for Computational Linguistics (2021)
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Maze Made Easy: Better and easier measurement of incremental processing difficulty
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In: Other repository (2021)
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Child-directed Listening: How Caregiver Inference Enables Children's Early Verbal Communication ...
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Child-directed Listening: How Caregiver Inference Enables Children's Early Verbal Communication.
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Do domain-general executive resources play a role in linguistic prediction? Re-evaluation of the evidence and a path forward
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In: Prof. Fedorenko (2021)
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Pronoun interpretation in Mandarin Chinese follows principles of Bayesian inference
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In: PLoS (2021)
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Assessing Language Proficiency from Eye Movements in Reading
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In: Association for Computational Linguistics (2021)
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Implicit Gender Bias in Linguistic Descriptions for Expected Events: The Cases of the 2016 United States and 2017 United Kingdom Elections
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In: Sage (2021)
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Language Learning and Processing in People and Machines
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In: Association for Computational Linguistics (2021)
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Lossy‐Context Surprisal: An Information‐Theoretic Model of Memory Effects in Sentence Processing
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In: Wiley (2021)
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A Targeted Assessment of Incremental Processing in Neural LanguageModels and Humans ...
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A Rate–Distortion view of human pragmatic reasoning
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In: Proceedings of the Society for Computation in Linguistics (2021)
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Implicit Gender Bias in Linguistic Descriptions for Expected Events: The Cases of the 2016 United States and 2017 United Kingdom Elections ...
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