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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 61 – 80 of 163 61 Differentiable subset pruning of transformer heads Li, Jiaoda; Cotterell, Ryan; Sachan, Mrinmaya In: Transactions of the Association for Computational Linguistics, 9 (2021) BASE Show details 62 Parameter space factorization for zero-shot learning across tasks and languages Parovic, Marinela; Cotterell, Ryan; Vulić, Ivan... In: Transactions of the Association for Computational Linguistics, 9 (2021) BASE Show details 63 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 64 Searching for More Efficient Dynamic Programs Cotterell, Ryan; Eisner, Jason; Vieira, Tim In: Findings of the Association for Computational Linguistics: EMNLP 2021 (2021) BASE Show details 65 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 66 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) Abstract: Pimentel et al. (2020) recently analysed probing from an information-theoretic perspective. They argue that probing should be seen as approximating a mutual information. This led to the rather unintuitive conclusion that representations encode exactly the same information about a target task as the original sentences. The mutual information, however, assumes the true probability distribution of a pair of random variables is known, leading to unintuitive results in settings where it is not. This paper proposes a new framework to measure what we term Bayesian mutual information, which analyses information from the perspective of Bayesian agents—allowing for more intuitive findings in scenarios with finite data. For instance, under Bayesian MI we have that data can add information, processing can help, and information can hurt, which makes it more intuitive for machine learning applications. Finally, we apply our framework to probing where we believe Bayesian mutual information naturally operationalises ease of extraction by explicitly limiting the available background knowledge to solve a task. URL: https://doi.org/10.3929/ethz-b-000518995 https://hdl.handle.net/20.500.11850/518995 BASE Hide details 67 Examining the Inductive Bias of Neural Language Models with Artificial Languages White, Jennifer C.; Cotterell, Ryan In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (2021) BASE Show details 68 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 69 How (Non-)Optimal is the Lexicon? ... NAACL 2021 2021; Blasi, Damián; Cotterell, Ryan. - : Underline Science Inc., 2021 BASE Show details 70 A Cognitive Regularizer for Language Modeling ... 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; Cotterell, Ryan; Meister, Clara. - : Underline Science Inc., 2021 BASE Show details 71 Do Syntactic Probes Probe Syntax? Experiments with Jabberwocky Probing ... Hall Maudslay, Rowan; Cotterell, Ryan. - : ETH Zurich, 2021 BASE Show details 72 Do Syntactic Probes Probe Syntax? Experiments with Jabberwocky Probing ... Maudslay, Rowan Hall; Cotterell, Ryan. - : arXiv, 2021 BASE Show details 73 A Non-Linear Structural Probe ... White, Jennifer C.; Pimentel, Tiago; Saphra, Naomi. - : ETH Zurich, 2021 BASE Show details 74 A Cognitive Regularizer for Language Modeling ... Wei, Jason; Meister, Clara Isabel; Cotterell, Ryan. - : ETH Zurich, 2021 BASE Show details 75 How (Non-)Optimal is the Lexicon? ... Pimentel, Tiago; Nikkarinen, Irene; Mahowald, Kyle. - : ETH Zurich, 2021 BASE Show details 76 Disambiguatory Signals are Stronger in Word-initial Positions ... Pimentel, Tiago; Cotterell, Ryan; Roark, Brian. - : ETH Zurich, 2021 BASE Show details 77 Finding Concept-specific Biases in Form--Meaning Associations ... NAACL 2021 2021; Blasi, Damián; Cotterell, Ryan. - : Underline Science Inc., 2021 BASE Show details 78 Backtranslation feedback improves user confidence in MT, not quality Obregón, Mateo; Fomicheva, Marina; Novák, Michal. - : Association for Computational Linguistics, 2021 BASE Show details 79 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 80 Investigating Cross-Linguistic Adjective Ordering Tendencies with a Latent-Variable Model ... Leung, Jun Yen; Emerson, Guy; Cotterell, Ryan. - : arXiv, 2020 BASE Show details Page: 1 2 3 4 5 6 7 8 9

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