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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 Page: 1 2 3 Hits 1 – 20 of 58 1 How Efficiency Shapes Human Language Gibson, Edward; Futrell, Richard; Piantadosi, Steven... In: https://hal.archives-ouvertes.fr/hal-03552539 ; 2022 (2022) BASE Show details 2 A verb-frame frequency account of constraints on long-distance dependencies in English Liu, Yingtong; Ryskin, Rachel; Futrell, Richard... In: Prof. Gibson (2022) BASE Show details 3 Dependency locality as an explanatory principle for word order Futrell, Richard; Levy, Roger P; Gibson, Edward A In: Prof. Levy (2022) BASE Show details 4 When classifying grammatical role, BERT doesn't care about word order... except when it matters ... Papadimitriou, Isabel; Futrell, Richard; Mahowald, Kyle. - : arXiv, 2022 BASE Show details 5 Grammatical cues are largely, but not completely, redundant with word meanings in natural language ... Mahowald, Kyle; Diachek, Evgeniia; Gibson, Edward. - : arXiv, 2022 BASE Show details 6 Learning Constraints on Wh-Dependencies by Learning How to Efficiently Represent Wh-Dependencies: A Developmental Modeling Investigation With Fragment Grammars Dickson, Niels; Pearl, Lisa; Futrell, Richard In: Proceedings of the Society for Computation in Linguistics (2022) BASE Show details 7 When Classifying Arguments, BERT Doesn't Care About Word Order. Except When It Matters Papadimitriou, Isabel; Futrell, Richard; Mahowald, Kyle In: Proceedings of the Society for Computation in Linguistics (2022) BASE Show details 8 Word order affects the frequency of adjective use across languages Kachakeche, Zeinab; Futrell, Richard; Scontras, Gregory In: Proceedings of the Annual Meeting of the Cognitive Science Society, vol 43, iss 43 (2021) BASE Show details 9 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 10 Hierarchical Representation in Neural Language Models: Suppression and Recovery of Expectations Wilcox, Ethan; Levy, Roger P; Futrell, Richard In: Association for Computational Linguistics (2021) BASE Show details 11 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 12 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 13 Structural Supervision Improves Learning of Non-Local Grammatical Dependencies Wilcox, Ethan; Qian, Peng; Futrell, Richard... In: Association for Computational Linguistics (2021) BASE Show details 14 Maze Made Easy: Better and easier measurement of incremental processing difficulty Boyce, Veronica; Futrell, Richard; Levy, Roger P In: Other repository (2021) BASE Show details 15 An Information-Theoretic Characterization of Morphological Fusion ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Futrell, Richard; Hahn, Michael. - : Underline Science Inc., 2021 BASE Show details 16 Deep Subjecthood: Higher-Order Grammatical Features in Multilingual BERT ... Papadimitriou, Isabel; Chi, Ethan A.; Futrell, Richard. - : arXiv, 2021 BASE Show details 17 Multilingual BERT, Ergativity, and Grammatical Subjecthood ... Papadimitriou, Isabel; Chi, Ethan A.; Futrell, Richard. - : University of Massachusetts Amherst, 2021 BASE Show details 18 Sensitivity as a Complexity Measure for Sequence Classification Tasks ... Hahn, Michael; Jurafsky, Dan; Futrell, Richard. - : arXiv, 2021 Abstract: We introduce a theoretical framework for understanding and predicting the complexity of sequence classification tasks, using a novel extension of the theory of Boolean function sensitivity. The sensitivity of a function, given a distribution over input sequences, quantifies the number of disjoint subsets of the input sequence that can each be individually changed to change the output. We argue that standard sequence classification methods are biased towards learning low-sensitivity functions, so that tasks requiring high sensitivity are more difficult. To that end, we show analytically that simple lexical classifiers can only express functions of bounded sensitivity, and we show empirically that low-sensitivity functions are easier to learn for LSTMs. We then estimate sensitivity on 15 NLP tasks, finding that sensitivity is higher on challenging tasks collected in GLUE than on simple text classification tasks, and that sensitivity predicts the performance both of simple lexical classifiers and of vanilla ... : Accepted by TACL. This is a pre-MIT Press publication version ... Keyword: Computation and Language cs.CL; Computational Complexity cs.CC; FOS Computer and information sciences; Machine Learning cs.LG URL: https://dx.doi.org/10.48550/arxiv.2104.10343 https://arxiv.org/abs/2104.10343 BASE Hide details 19 What do RNN Language Models Learn about Filler–Gap Dependencies? Wilcox, Ethan; Levy, Roger; Morita, Takashi... In: Association for Computational Linguistics (2021) BASE Show details 20 Language Learning and Processing in People and Machines Nematzadeh, Aida; Futrell, Richard; Levy, Roger P In: Association for Computational Linguistics (2021) BASE Show details Page: 1 2 3

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