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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 A Latent-Variable Model for Intrinsic Probing ... Stańczak, Karolina; Hennigen, Lucas Torroba; Williams, Adina. - : arXiv, 2022 BASE Show details 2 Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionality ... Thrush, Tristan; Jiang, Ryan; Bartolo, Max. - : arXiv, 2022 BASE Show details 3 ANLIzing the Adversarial Natural Language Inference Dataset Williams, Adina; Thrush, Tristan; Kiela, Douwe In: Proceedings of the Society for Computation in Linguistics (2022) BASE Show details 4 Investigating Failures of Automatic Translation in the Case of Unambiguous Gender ... Renduchintala, Adithya; Williams, Adina. - : arXiv, 2021 BASE Show details 5 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 6 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 7 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 8 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 9 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 10 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. - : Underline Science Inc., 2021 BASE Show details 11 On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs ... Williams, Adina; Cotterell, Ryan; Wolf-Sonkin, Lawrence. - : arXiv, 2020 BASE Show details 12 SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection ... Vylomova, Ekaterina; White, Jennifer; Salesky, Elizabeth. - : arXiv, 2020 BASE Show details 13 Intrinsic Probing through Dimension Selection ... Hennigen, Lucas Torroba; Williams, Adina; Cotterell, Ryan. - : arXiv, 2020 BASE Show details 14 Information-Theoretic Probing for Linguistic Structure ... Pimentel, Tiago; Valvoda, Josef; Maudslay, Rowan Hall. - : arXiv, 2020 BASE Show details 15 Information-Theoretic Probing for Linguistic Structure ... Pimentel, Tiago; Valvoda, Josef; Maudslay, Rowan H.; Zmigrod, Ran; Williams, Adina; Cotterell, Ryan. - : ETH Zurich, 2020 Abstract: The success of neural networks on a diverse set of NLP tasks has led researchers to question how much these networks actually "know" about natural language. Probes are a natural way of assessing this. When probing, a researcher chooses a linguistic task and trains a supervised model to predict annotations in that linguistic task from the network's learned representations. If the probe does well, the researcher may conclude that the representations encode knowledge related to the task. A commonly held belief is that using simpler models as probes is better; the logic is that simpler models will identify linguistic structure, but not learn the task itself. We propose an information-theoretic operationalization of probing as estimating mutual information that contradicts this received wisdom: one should always select the highest performing probe one can, even if it is more complex, since it will result in a tighter estimate, and thus reveal more of the linguistic information inherent in the representation. The ... : Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics ... URL: http://hdl.handle.net/20.500.11850/446005 https://dx.doi.org/10.3929/ethz-b-000446005 BASE Hide details 16 Intrinsic Probing through Dimension Selection ... Torroba Hennigen, Lucas; Williams, Adina; Cotterell, Ryan. - : ETH Zurich, 2020 BASE Show details 17 Predicting Declension Class from Form and Meaning ... Williams, Adina; Pimentel, Tiago; McCarthy, Arya D.. - : arXiv, 2020 BASE Show details 18 Predicting declension class from form and meaning Williams, Adina; Pimentel, Tiago; McCarthy, Arya. - 2020 BASE Show details 19 Measuring the Similarity of Grammatical Gender Systems by Comparing Partitions McCarthy, Arya D.; Cotterell, Ryan; Williams, Adina... In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020) BASE Show details 20 Pareto Probing: Trading Off Accuracy for Complexity Saphra, Naomi; Cotterell, Ryan; Pimentel, Tiago... In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020) BASE Show details Page: 1 2 3

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