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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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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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Abstract:
We present a novel approach for determining learners' second language proficiency which utilizes behavioral traces of eye movements during reading. Our approach provides standalone eyetracking based English proficiency scores which reflect the extent to which the learner's gaze patterns in reading are similar to those of native English speakers. We show that our scores correlate strongly with standardized English proficiency tests. We also demonstrate that gaze information can be used to accurately predict the outcomes of such tests. Our approach yields the strongest performance when the test taker is presented with a suite of sentences for which we have eyetracking data from other readers. However, it remains effective even using eyetracking with sentences for which eye movement data have not been previously collected. By deriving proficiency as an automatic byproduct of eye movements during ordinary reading, our approach offers a potentially valuable new tool for second language proficiency assessment. More broadly, our results open the door to future methods for inferring reader characteristics from the behavioral traces of reading.
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URL: https://hdl.handle.net/1721.1/130436
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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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