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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 39 1 Probing for the Usage of Grammatical Number ... Lasri, Karim; Pimentel, Tiago; Lenci, Alessandro. - : arXiv, 2022 BASE Show details 2 On Homophony and Rényi Entropy ... Pimentel, Tiago; Meister, Clara Isabel; Teufel, Simone. - : ETH Zurich, 2021 BASE Show details 3 On Homophony and Rényi Entropy ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Cotterell, Ryan; Meister, Clara. - : Underline Science Inc., 2021 BASE Show details 4 Revisiting the Uniform Information Density Hypothesis ... Meister, Clara; Pimentel, Tiago; Haller, Patrick. - : arXiv, 2021 BASE Show details 5 Revisiting the Uniform Information Density Hypothesis ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Cotterell, Ryan; Haller, Patrick. - : Underline Science Inc., 2021 BASE Show details 6 Modeling the Unigram Distribution ... 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; Blasi, Damián; Cotterell, Ryan; Nikkarinen, Irene; Pimentel, Tiago. - : Underline Science Inc., 2021 Abstract: Read paper: https://www.aclanthology.org/2021.findings-acl.326 Abstract: The unigram distribution is the non-contextual probability of finding a specific word form in a corpus. While of central importance to the study of language, it is commonly approximated by each word's sample frequency in the corpus. This approach, being highly dependent on sample size, assigns zero probability to any out-of-vocabulary (oov) word form. As a result, it produces negatively biased probabilities for any oov word form, while positively biased probabilities to in-corpus words. In this work, we argue in favor of properly modeling the unigram distribution---claiming it should be a central task in natural language processing. With this in mind, we present a novel model for estimating it in a language (a neuralization of Goldwater et al.'s (2011) model) and show it produces much better estimates across a diverse set of 7 languages than the naïive use of neural character-level language models. ... URL: https://dx.doi.org/10.48448/fx5z-4a29 https://underline.io/lecture/26417-modeling-the-unigram-distribution BASE Hide details 7 A Bayesian Framework for Information-Theoretic Probing ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Cotterell, Ryan; Pimentel, Tiago. - : Underline Science Inc., 2021 BASE Show details 8 A surprisal--duration trade-off across and within the world's languages ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Blasi, Damián; Cotterell, Ryan. - : Underline Science Inc., 2021 BASE Show details 9 Revisiting the Uniform Information Density Hypothesis ... Meister, Clara Isabel; Pimentel, Tiago; Haller, Patrick. - : ETH Zurich, 2021 BASE Show details 10 What About the Precedent: An Information-Theoretic Analysis of Common Law ... Valvoda, Josef; Pimentel, Tiago; Stoehr, Niklas. - : ETH Zurich, 2021 BASE Show details 11 Modeling the Unigram Distribution ... Nikkarinen, Irene; Pimentel, Tiago; Blasi, Damián. - : ETH Zurich, 2021 BASE Show details 12 Finding Concept-specific Biases in Form–Meaning Associations ... Pimentel, Tiago; Roark, Brian; Wichmann, Søren. - : ETH Zurich, 2021 BASE Show details 13 Modeling the Unigram Distribution Blasi, Damián; Pimentel, Tiago; Nikkarinen, Irene... In: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (2021) BASE Show details 14 What About the Precedent: An Information-Theoretic Analysis of Common Law Teufel, Simone; Valvoda, Josef; Stoehr, Niklas... In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021) BASE Show details 15 Finding Concept-specific Biases in Form–Meaning Associations Roark, Brian; Blasi, Damián; Pimentel, Tiago... In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021) BASE Show details 16 A Non-Linear Structural Probe Pimentel, Tiago; Cotterell, Ryan; Saphra, Naomi... In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021) BASE Show details 17 Disambiguatory Signals are Stronger in Word-initial Positions Pimentel, Tiago; Cotterell, Ryan; Roark, Brian In: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume (2021) BASE Show details 18 How (Non-)Optimal is the Lexicon? Cotterell, Ryan; Pimentel, Tiago; Nikkarinen, Irene... In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021) BASE Show details 19 A Bayesian Framework for Information-Theoretic Probing Cotterell, Ryan; Pimentel, Tiago In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021) BASE Show details 20 How (Non-)Optimal is the Lexicon? ... NAACL 2021 2021; Blasi, Damián; Cotterell, Ryan. - : Underline Science Inc., 2021 BASE Show details Page: 1 2

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