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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 4 5 Hits 1 – 20 of 86 1 Formal Language Recognition by Hard Attention Transformers: Perspectives from Circuit Complexity ... Hao, Yiding; Angluin, Dana; Frank, Robert. - : arXiv, 2022 BASE Show details 2 Do Language Models Learn Position-Role Mappings? ... Petty, Jackson; Wilson, Michael; Frank, Robert. - : arXiv, 2022 BASE Show details 3 Coloring the Blank Slate: Pre-training Imparts a Hierarchical Inductive Bias to Sequence-to-sequence Models ... Mueller, Aaron; Frank, Robert; Linzen, Tal. - : arXiv, 2022 BASE Show details 4 Arguments for top-down derivations in syntax Frank, Robert; Kotek, Hadas In: Proceedings of the Linguistic Society of America; Vol 7, No 1 (2022): Proceedings of the Linguistic Society of America; 5264 ; 2473-8689 (2022) BASE Show details 5 Structure Here, Bias There: Hierarchical Generalization by Jointly Learning Syntactic Transformations Mulligan, Karl; Frank, Robert; Linzen, Tal In: Proceedings of the Society for Computation in Linguistics (2021) BASE Show details 6 Comparing methods of tree-construction across mildly context-sensitive formalisms Hunter, Tim; Frank, Robert In: Proceedings of the Society for Computation in Linguistics (2021) BASE Show details 7 The Role of Linguistic Features in Domain Adaptation: TAG Parsing of Questions ... Srivastava, Aarohi; Frank, Robert; Widder, Sarah. - : University of Mass Amherst, 2020 BASE Show details 8 Sequence-to-Sequence Networks Learn the Meaning of Reflexive Anaphora ... Frank, Robert; Petty, Jackson. - : arXiv, 2020 BASE Show details 9 Sequence-to-Sequence Networks Learn the Meaning of Reflexive Anaphora ... The 28th International Conference on Computational Linguistics 2020; Frank, Robert; Petty, Jackson. - : Underline Science Inc., 2020 BASE Show details 10 Probabilistic Predictions of People Perusing: Evaluating Metrics of Language Model Performance for Psycholinguistic Modeling ... Hao, Yiding; Mendelsohn, Simon; Sterneck, Rachel. - : arXiv, 2020 BASE Show details 11 The Role of Linguistic Features in Domain Adaptation: TAG Parsing of Questions Srivastava, Aarohi; Frank, Robert; Widder, Sarah... In: Proceedings of the Society for Computation in Linguistics (2020) BASE Show details 12 Primitive Asymmetric C-Command Derives X̄-Theory Frank, Robert; Kuminiak, Fero In: North East Linguistics Society (2020) BASE Show details 13 Does Syntax Need to Grow on Trees? Sources of Hierarchical Inductive Bias in Sequence-to-Sequence Networks McCoy, R. Thomas; Frank, Robert; Linzen, Tal In: Transactions of the Association for Computational Linguistics, Vol 8, Pp 125-140 (2020) (2020) BASE Show details 14 Jabberwocky Parsing: Dependency Parsing with Lexical Noise ... Kasai, Jungo; Frank, Robert. - : University of Massachusetts Amherst, 2019 BASE Show details 15 Open Sesame: Getting Inside BERT's Linguistic Knowledge ... Lin, Yongjie; Tan, Yi Chern; Frank, Robert. - : arXiv, 2019 BASE Show details 16 Finding Syntactic Representations in Neural Stacks ... Merrill, William; Khazan, Lenny; Amsel, Noah. - : arXiv, 2019 BASE Show details 17 A Unified Analysis of Reflexives and Reciprocals in Synchronous Tree Adjoining Grammar Aggazzotti, Cristina. - 2019 BASE Show details 18 Jabberwocky Parsing: Dependency Parsing with Lexical Noise Kasai, Jungo; Frank, Robert In: Proceedings of the Society for Computation in Linguistics (2019) BASE Show details 19 Revisiting the poverty of the stimulus: hierarchical generalization without a hierarchical bias in recurrent neural networks ... McCoy, R. Thomas; Frank, Robert; Linzen, Tal. - : arXiv, 2018 Abstract: Syntactic rules in natural language typically need to make reference to hierarchical sentence structure. However, the simple examples that language learners receive are often equally compatible with linear rules. Children consistently ignore these linear explanations and settle instead on the correct hierarchical one. This fact has motivated the proposal that the learner's hypothesis space is constrained to include only hierarchical rules. We examine this proposal using recurrent neural networks (RNNs), which are not constrained in such a way. We simulate the acquisition of question formation, a hierarchical transformation, in a fragment of English. We find that some RNN architectures tend to learn the hierarchical rule, suggesting that hierarchical cues within the language, combined with the implicit architectural biases inherent in certain RNNs, may be sufficient to induce hierarchical generalizations. The likelihood of acquiring the hierarchical generalization increased when the language included an ... : Proceedings of the 40th Annual Conference of the Cognitive Science Society; 10 pages ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/1802.09091 https://dx.doi.org/10.48550/arxiv.1802.09091 BASE Hide details 20 Phonologically Informed Edit Distance Algorithms for Word Alignment with Low-Resource Languages ... McCoy, Richard T.; Frank, Robert. - : University of Massachusetts Amherst, 2018 BASE Show details Page: 1 2 3 4 5

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