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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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Granularity in the Semantics of Comparison
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In: Semantics and Linguistic Theory; Proceedings of SALT 31; 550-569 ; 2163-5951 (2022)
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Competition from novel features drives scalar inferences in reference games
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In: Proceedings of the Annual Meeting of the Cognitive Science Society, vol 43, iss 43 (2021)
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Using the Interpolated Maze Task to Assess Incremental Processing in English Relative Clauses
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In: Proceedings of the Annual Meeting of the Cognitive Science Society, vol 43, iss 43 (2021)
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Child-directed Listening: How Caregiver Inference Enables Children's Early Verbal Communication
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In: Proceedings of the Annual Meeting of the Cognitive Science Society, vol 43, iss 43 (2021)
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On Factors Influencing Typing Time: Insights from a Viral Online Typing Game
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In: Proceedings of the Annual Meeting of the Cognitive Science Society, vol 43, iss 43 (2021)
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Eye Movement Traces of Linguistic Knowledge
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In: Proceedings of the Annual Meeting of the Cognitive Science Society, vol 43, iss 43 (2021)
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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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SyntaxGym: An Online Platform for Targeted Evaluation of Language Models
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In: Association for Computational Linguistics (2021)
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Abstract:
Targeted syntactic evaluations have yielded insights into the generalizations learned by neural network language models. However, this line of research requires an uncommon confluence of skills: both the theoretical knowledge needed to design controlled psycholinguistic experiments, and the technical proficiency needed to train and deploy large-scale language models. We present SyntaxGym, an online platform designed to make targeted evaluations accessible to both experts in NLP and linguistics, reproducible across computing environments, and standardized following the norms of psycholinguistic experimental design. This paper releases two tools of independent value for the computational linguistics community: 1. A website, syntaxgym.org, which centralizes the process of targeted syntactic evaluation and provides easy tools for analysis and visualization; 2. Two command-line tools, syntaxgym and lm-zoo, which allow any user to reproduce targeted syntactic evaluations and general language model inference on their own machine.
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URL: https://hdl.handle.net/1721.1/138281
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Comparing Models of Associative Meaning: An Empirical Investigation of Reference in Simple Language Games
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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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Investigating Novel Verb Learning in BERT: Selectional Preference Classes and Alternation-Based Syntactic Generalization
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In: Association for Computational Linguistics (2021)
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Representation of Constituents in Neural Language Models: Coordination Phrase as a Case Study
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In: Association for Computational Linguistics (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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Structural Supervision Improves Few-Shot Learning and Syntactic Generalization in Neural 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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Linking artificial and human neural representations of language
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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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