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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 – 4 of 4 1 Child-directed Listening: How Caregiver Inference Enables Children's Early Verbal Communication ... Meylan, Stephan C.; Foushee, Ruthe; Bergelson, Elika. - : arXiv, 2021 BASE Show details 2 A Targeted Assessment of Incremental Processing in Neural LanguageModels and Humans ... Wilcox, Ethan Gotlieb; Vani, Pranali; Levy, Roger P.. - : arXiv, 2021 BASE Show details 3 Towards a Referential Theory of Ellipsis Poppels, Till. - : eScholarship, University of California, 2020 BASE Show details 4 A Systematic Assessment of Syntactic Generalization in Neural Language Models ... Hu, Jennifer; Gauthier, Jon; Qian, Peng; Wilcox, Ethan; Levy, Roger P.. - : arXiv, 2020 Abstract: While state-of-the-art neural network models continue to achieve lower perplexity scores on language modeling benchmarks, it remains unknown whether optimizing for broad-coverage predictive performance leads to human-like syntactic knowledge. Furthermore, existing work has not provided a clear picture about the model properties required to produce proper syntactic generalizations. We present a systematic evaluation of the syntactic knowledge of neural language models, testing 20 combinations of model types and data sizes on a set of 34 English-language syntactic test suites. We find substantial differences in syntactic generalization performance by model architecture, with sequential models underperforming other architectures. Factorially manipulating model architecture and training dataset size (1M--40M words), we find that variability in syntactic generalization performance is substantially greater by architecture than by dataset size for the corpora tested in our experiments. Our results also reveal a ... : To appear in the Proceedings of the Association for Computational Linguistics (ACL 2020) ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2005.03692 https://dx.doi.org/10.48550/arxiv.2005.03692 BASE Hide details

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