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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 4 5 6 7 8 9 Hits 81 – 100 of 163 81 SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection ... Vylomova, Ekaterina; White, Jennifer; Salesky, Elizabeth. - : arXiv, 2020 BASE Show details 82 Intrinsic Probing through Dimension Selection ... Hennigen, Lucas Torroba; Williams, Adina; Cotterell, Ryan. - : arXiv, 2020 BASE Show details 83 SIGTYP 2020 Shared Task: Prediction of Typological Features ... Bjerva, Johannes; Salesky, Elizabeth; Mielke, Sabrina J.. - : arXiv, 2020 BASE Show details 84 The Paradigm Discovery Problem ... Erdmann, Alexander; Elsner, Micha; Wu, Shijie. - : ETH Zurich, 2020 BASE Show details 85 Information-Theoretic Probing for Linguistic Structure ... Pimentel, Tiago; Valvoda, Josef; Maudslay, Rowan Hall. - : arXiv, 2020 BASE Show details 86 It’s Easier to Translate out of English than into it: Measuring Neural Translation Difficulty by Cross-Mutual Information ... Bugliarello, Emanuele; Mielke, Sabrina J.; Anastasopoulos, Antonios. - : ETH Zurich, 2020 BASE Show details 87 Information-Theoretic Probing for Linguistic Structure ... Pimentel, Tiago; Valvoda, Josef; Maudslay, Rowan H.. - : ETH Zurich, 2020 BASE Show details 88 Intrinsic Probing through Dimension Selection ... Torroba Hennigen, Lucas; Williams, Adina; Cotterell, Ryan. - : ETH Zurich, 2020 Abstract: Most modern NLP systems make use of pre-trained contextual representations that attain astonishingly high performance on a variety of tasks. Such high performance should not be possible unless some form of linguistic structure inheres in these representations, and a wealth of research has sprung up on probing for it. In this paper, we draw a distinction between intrinsic probing, which examines how linguistic information is structured within a representation, and the extrinsic probing popular in prior work, which only argues for the presence of such information by showing that it can be successfully extracted. To enable intrinsic probing, we propose a novel framework based on a decomposable multivariate Gaussian probe that allows us to determine whether the linguistic information in word embeddings is dispersed or focal. We then probe fastText and BERT for various morphosyntactic attributes across 36 languages. We find that most attributes are reliably encoded by only a few neurons, with fastText ... : Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) ... URL: http://hdl.handle.net/20.500.11850/462314 https://dx.doi.org/10.3929/ethz-b-000462314 BASE Hide details 89 Generalized Entropy Regularization or: There’s Nothing Special about Label Smoothing ... Meister, Clara Isabel; Salesky, Elizabeth; Cotterell, Ryan. - : ETH Zurich, 2020 BASE Show details 90 A Corpus for Large-Scale Phonetic Typology ... Salesky, Elizabeth; Chodroff, Eleanor; Pimentel, Tiago. - : arXiv, 2020 BASE Show details 91 Phonotactic Complexity and its Trade-offs ... Pimentel, Tiago; Roark, Brian; Cotterell, Ryan. - : arXiv, 2020 BASE Show details 92 Phonotactic Complexity and Its Trade-offs ... Pimentel, Tiago; Roark, Brian; Cotterell, Ryan. - : ETH Zurich, 2020 BASE Show details 93 A Corpus for Large-Scale Phonetic Typology ... Salesky, Elizabeth; Chodroff, Eleanor; Pimentel, Tiago. - : ETH Zurich, 2020 BASE Show details 94 Investigating Cross-Linguistic Adjective Ordering Tendencies with a Latent-Variable Model ... Leung, Jun Yen; Emerson, Guy; Cotterell, Ryan. - : ETH Zurich, 2020 BASE Show details 95 Morphologically Aware Word-Level Translation ... Czarnowska, Paula; Ruder, Sebastian; Cotterell, Ryan. - : arXiv, 2020 BASE Show details 96 Predicting Declension Class from Form and Meaning ... Williams, Adina; Pimentel, Tiago; McCarthy, Arya D.. - : arXiv, 2020 BASE Show details 97 Predicting declension class from form and meaning Williams, Adina; Pimentel, Tiago; McCarthy, Arya. - 2020 BASE Show details 98 Please Mind the Root: Decoding Arborescences for Dependency Parsing Vieira, Tim; Cotterell, Ryan; Zmigrod, Ran In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020) BASE Show details 99 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 100 Investigating Cross-Linguistic Adjective Ordering Tendencies with a Latent-Variable Model Emerson, Guy; Cotterell, Ryan; Leung, Jun Yen In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020) BASE Show details Page: 1 2 3 4 5 6 7 8 9

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