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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 23 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) Abstract: We perform an in-depth error analysis of the Adversarial NLI (ANLI) dataset, a recently introduced large-scale human-and-model-in-the-loop natural language inference dataset collected dynamically over multiple rounds. We propose a fine-grained annotation scheme for the different aspects of inference responsible for the gold classification labels, and use it to hand-code the ANLI development sets in their entirety. We use these annotations to answer a variety of important questions: which models have the highest performance on each inference type, which inference types are most common, and which types are the most challenging for state-of-the-art models? We hope our annotations will enable more fine-grained evaluation of NLI models, and provide a deeper understanding of where models fail (and succeed). Both insights can guide us in training stronger models going forward. Keyword: annotation; artificial neural networks; Computational Linguistics; corpora; machine learning; natural language inference; natural language understanding; neural networks URL: https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1250&context=scil https://scholarworks.umass.edu/scil/vol5/iss1/4 BASE Hide details 4 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 5 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 6 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 7 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 8 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 9 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 10 Information-Theoretic Probing for Linguistic Structure ... Pimentel, Tiago; Valvoda, Josef; Maudslay, Rowan H.. - : ETH Zurich, 2020 BASE Show details 11 Intrinsic Probing through Dimension Selection ... Torroba Hennigen, Lucas; Williams, Adina; Cotterell, Ryan. - : ETH Zurich, 2020 BASE Show details 12 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 13 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 14 Predicting Declension Class from Form and Meaning Cotterell, Ryan; Blix, Hagen; Pimentel, Tiago... In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020) BASE Show details 15 A Tale of a Probe and a Parser Valvoda, Josef; Hall Maudslay, Rowan; Williams, Adina... In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020) BASE Show details 16 Intrinsic Probing through Dimension Selection Cotterell, Ryan; Williams, Adina; Torroba Hennigen, Lucas In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020) BASE Show details 17 Information-Theoretic Probing for Linguistic Structure Pimentel, Tiago; Zmigrod, Ran; Cotterell, Ryan... In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020) BASE Show details 18 A Tale of a Probe and a Parser ... Hall Maudslay, Rowan; Valvoda, Josef; Pimentel, Tiago. - : ETH Zurich, 2020 BASE Show details 19 Measuring the Similarity of Grammatical Gender Systems by Comparing Partitions ... McCarthy, Arya D.; Williams, Adina; Liu, Shijia. - : ETH Zurich, 2020 BASE Show details 20 Predicting Declension Class from Form and Meaning ... Williams, Adina; Pimentel, Tiago; Blix, Hagen. - : ETH Zurich, 2020 BASE Show details Page: 1 2

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