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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... In: Association for Computational Linguistics (2021) BASE Show 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; Qian, Peng. - : arXiv, 2021 Abstract: Prior work has shown that structural supervision helps English language models learn generalizations about syntactic phenomena such as subject-verb agreement. However, it remains unclear if such an inductive bias would also improve language models' ability to learn grammatical dependencies in typologically different languages. Here we investigate this question in Mandarin Chinese, which has a logographic, largely syllable-based writing system; different word order; and sparser morphology than English. We train LSTMs, Recurrent Neural Network Grammars, Transformer language models, and Transformer-parameterized generative parsing models on two Mandarin Chinese datasets of different sizes. We evaluate the models' ability to learn different aspects of Mandarin grammar that assess syntactic and semantic relationships. We find suggestive evidence that structural supervision helps with representing syntactic state across intervening content and improves performance in low-data settings, suggesting that the benefits ... : To appear in the Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021) ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2109.11058 https://dx.doi.org/10.48550/arxiv.2109.11058 BASE Hide 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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