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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 17 of 17 1 Syntactic dependencies correspond to word pairs with high mutual information Futrell, Richard; Qian, Peng; Gibson, Edward A... In: Association for Computational Linguistics (2021) BASE Show details 2 A Systematic Assessment of Syntactic Generalization in Neural Language Models Hu, Jennifer; Gauthier, Jon; Qian, Peng... In: Association for Computational Linguistics (2021) BASE Show details 3 SyntaxGym: An Online Platform for Targeted Evaluation of Language Models Gauthier, Jon; Hu, Jennifer; Wilcox, Ethan; Qian, Peng; Levy, Roger In: Association for Computational Linguistics (2021) 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. URL: https://hdl.handle.net/1721.1/138281 BASE Hide details 4 Representation of Constituents in Neural Language Models: Coordination Phrase as a Case Study An, Aixiu; Qian, Peng; Wilcox, Ethan... In: Association for Computational Linguistics (2021) BASE Show details 5 SyntaxGym: An Online Platform for Targeted Evaluation of Language Models Gauthier, Jon; Hu, Jennifer; Wilcox, Ethan... In: Association for Computational Linguistics (2021) BASE Show details 6 Structural Supervision Improves Few-Shot Learning and Syntactic Generalization in Neural Language Models Wilcox, Ethan; Futrell, Richard; Qian, Peng... In: Association for Computational Linguistics (2021) BASE Show details 7 Neural language models as psycholinguistic subjects: Representations of syntactic state Levy, Roger P; Qian, Peng In: Association for Computational Linguistics (2021) BASE Show details 8 Syntactic dependencies correspond to word pairs with high mutual information Futrell, Richard; Qian, Peng; Gibson, Edward... In: Association for Computational Linguistics (2021) BASE Show details 9 Structural Supervision Improves Learning of Non-Local Grammatical Dependencies Wilcox, Ethan; Qian, Peng; Futrell, Richard... In: Association for Computational Linguistics (2021) BASE Show details 10 Controlled Evaluation of Grammatical Knowledge in Mandarin Chinese Language Models ... Wang, Yiwen; Hu, Jennifer; Levy, Roger. - : arXiv, 2021 BASE Show details 11 Controlled Evaluation of Grammatical Knowledge in Mandarin Chinese Language Models ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Hu, Jennifer; Levy, Roger. - : Underline Science Inc., 2021 BASE Show details 12 What if This Modified That? Syntactic Interventions with Counterfactual Embeddings ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Levy, Roger; Qian, Peng. - : Underline Science Inc., 2021 BASE Show details 13 Structural Guidance for Transformer Language Models ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Astudillo, Ramón Fernandez; Levy, Roger. - : Underline Science Inc., 2021 BASE Show details 14 Structural Guidance for Transformer Language Models ... Qian, Peng; Naseem, Tahira; Levy, Roger. - : arXiv, 2021 BASE Show details 15 A Systematic Assessment of Syntactic Generalization in Neural Language Models ... Hu, Jennifer; Gauthier, Jon; Qian, Peng. - : arXiv, 2020 BASE Show details 16 Composition is the core driver of the language-selective network Mollica, Francis; Siegelman, Matthew; Diachek, Evgeniia... In: MIT Press (2019) BASE Show details 17 Representation of Constituents in Neural Language Models: Coordination Phrase as a Case Study ... An, Aixiu; Qian, Peng; Wilcox, Ethan. - : arXiv, 2019 BASE Show details

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