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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 – 7 of 7 1 Investigating Failures of Automatic Translation in the Case of Unambiguous Gender ... Renduchintala, Adithya; Williams, Adina. - : arXiv, 2021 BASE Show details 2 On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Blasi, Damián; Cotterell, Ryan. - : Underline Science Inc., 2021 BASE Show details 3 On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs ... Williams, Adina; Cotterell, Ryan; Wolf-Sonkin, Lawrence. - : ETH Zurich, 2021 BASE Show details 4 Generalising to German Plural Noun Classes, from the Perspective of a Recurrent Neural Network ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Dieuwke; ., Kate. - : Underline Science Inc., 2021 BASE Show details 5 On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs Williams, Adina; Blasi, Damián; Wallach, Hanna... In: Transactions of the Association for Computational Linguistics, 9 (2021) BASE Show details 6 UnNatural Language Inference ... 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; Parthasarathi, Prasanna; Pineau, Joelle. - : Underline Science Inc., 2021 BASE Show details 7 Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Dieuwke; Jia, Robin; Kiela, Douwe; Pineau, Joelle; Sinha, Koustuv; Williams, Adina. - : Underline Science Inc., 2021 Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.230/ Abstract: A possible explanation for the impressive performance of masked language model (MLM) pre-training is that such models have learned to represent the syntactic structures prevalent in classical NLP pipelines. In this paper, we propose a different explanation: MLMs succeed on downstream tasks almost entirely due to their ability to model higher-order word co-occurrence statistics. To demonstrate this, we pre-train MLMs on sentences with randomly shuffled word order, and show that these models still achieve high accuracy after fine-tuning on many downstream tasks -- including on tasks specifically designed to be challenging for models that ignore word order. Our models perform surprisingly well according to some parametric syntactic probes, indicating possible deficiencies in how we test representations for syntactic information. Overall, our results show that purely distributional information largely explains the success of ... Keyword: Computational Linguistics; Language Models; Machine Learning; Machine Learning and Data Mining; Natural Language Processing URL: https://dx.doi.org/10.48448/3r0a-fw32 https://underline.io/lecture/37423-masked-language-modeling-and-the-distributional-hypothesis-order-word-matters-pre-training-for-little BASE Hide details

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