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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 Hits 1 – 20 of 29 1 Can computers tell a story? Discourse Structure in Computer-generated Text and Humans Wey, Alex; Hemmatian, Babak; Avram, Rachel... In: Proceedings of the Annual Meeting of the Cognitive Science Society, vol 43, iss 43 (2021) BASE Show details 2 The Anatomy of Discourse: Linguistic Predictors of Narrative and Argument Quality Feucht, Sheridan; Hemmatian, Babak; Avram, Rachel... In: Proceedings of the Annual Meeting of the Cognitive Science Society, vol 43, iss 43 (2021) BASE Show details 3 The Anatomy of Discourse: Linguistic Predictors of Narrative and Argument Quality Motivation ... Feucht, Sheridan; Hemmatian, Babak; Avram, Rachel. - : Unpublished, 2021 BASE Show details 4 Which Linguist Invented the Lightbulb? Presupposition Verification for Question-Answering ... Kim, Najoung; Pavlick, Ellie; Ayan, Burcu Karagol. - : arXiv, 2021 BASE Show details 5 AND does not mean OR: Using Formal Languages to Study Language Models’ Representations ... 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; Feiman, Roman; Pavlick, Ellie. - : Underline Science Inc., 2021 BASE Show details 6 Which Linguist Invented the Lightbulb? Presupposition Verification for Question-Answering ... 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; Karagol Ayan, Burcu; Kim, Najoung. - : Underline Science Inc., 2021 BASE Show details 7 AND does not mean OR: Using Formal Languages to Study Language Models’ Representations ... 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; Feiman, Roman; Pavlick, Ellie. - : Underline Science Inc., 2021 BASE Show details 8 AND does not mean OR: Using Formal Languages to Study Language Models’ Representations ... 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; Feiman, Roman; Pavlick, Ellie. - : Underline Science Inc., 2021 BASE Show details 9 AND does not mean OR: Using Formal Languages to Study Language Models’ Representations ... 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; Feiman, Roman; Pavlick, Ellie. - : Underline Science Inc., 2021 BASE Show details 10 Can Language Models Encode Perceptual Structure Without Grounding? A Case Study in Color ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Abdou, Mostafa; Frank, Stella. - : Underline Science Inc., 2021 BASE Show details 11 The Anatomy of Discourse: Linguistic Predictors of Narrative and Argument Quality ... 43rd Annual Meeting of the Cognitive Science Society 2021; Avram, Rachel; Eickhoff, Carsten. - : Underline Science Inc., 2021 BASE Show details 12 Can computers tell a story? Discourse Structure in Computer-generated Text and Humans ... 43rd Annual Meeting of the Cognitive Science Society 2021; Avram, Rachel; Eickhoff, Carsten. - : Underline Science Inc., 2021 BASE Show details 13 Are Rotten Apples Edible? Challenging Commonsense Inference Ability with Exceptions ... 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; Do, Nam; Pavlick, Ellie. - : Underline Science Inc., 2021 BASE Show details 14 Does Vision-and-Language Pretraining Improve Lexical Grounding? ... Yun, Tian; Sun, Chen; Pavlick, Ellie. - : arXiv, 2021 BASE Show details 15 Does Vision-and-Language Pretraining Improve Lexical Grounding? ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Pavlick, Ellie; Sun, Chen. - : Underline Science Inc., 2021 BASE Show details 16 Does Vision-and-Language Pretraining Improve Lexical Grounding? ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Pavlick, Ellie; Sun, Chen. - : Underline Science Inc., 2021 BASE Show details 17 Frequency Effects on Syntactic Rule Learning in Transformers ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Garrette, Dan; Linzen, Tal; Pavlick, Ellie; Wei, Jason. - : Underline Science Inc., 2021 Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.72/ Abstract: Pre-trained language models perform well on a variety of linguistic tasks that require symbolic reasoning, raising the question of whether such models implicitly represent abstract symbols and rules. We investigate this question using the case study of BERT's performance on English subject-verb agreement. Unlike prior work, we train multiple instances of BERT from scratch, allowing us to perform a series of controlled interventions at pre-training time. We show that BERT often generalizes well to subject-verb pairs that never occurred in training, suggesting a degree of rule-governed behavior. We also find, however, that performance is heavily influenced by word frequency, with experiments showing that both the absolute frequency of a verb form, as well as the frequency relative to the alternate inflection, are causally implicated in the predictions BERT makes at inference time. Closer analysis of these frequency effects reveals ... Keyword: Cognitive Modeling; Computational Linguistics; Language Models; Machine Learning; Machine Learning and Data Mining; Natural Language Processing URL: https://underline.io/lecture/37826-frequency-effects-on-syntactic-rule-learning-in-transformers https://dx.doi.org/10.48448/pbd0-z377 BASE Hide details 18 Frequency Effects on Syntactic Rule Learning in Transformers ... Wei, Jason; Garrette, Dan; Linzen, Tal. - : arXiv, 2021 BASE Show details 19 Leveraging Longitudinal Data for Personalized Prediction and Word Representations Welch, Charles. - 2021 BASE Show details 20 A Visuospatial Dataset for Naturalistic Verb Learning ... Ebert, Dylan; Pavlick, Ellie. - : arXiv, 2020 BASE Show details Page: 1 2

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