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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 22 1 Estimating the Entropy of Linguistic Distributions ... Arora, Aryaman; Meister, Clara; Cotterell, Ryan. - : arXiv, 2022 BASE Show details 2 On Homophony and Rényi Entropy ... Pimentel, Tiago; Meister, Clara Isabel; Teufel, Simone. - : ETH Zurich, 2021 BASE Show details 3 On Homophony and Rényi Entropy ... Pimentel, Tiago; Meister, Clara; Teufel, Simone. - : arXiv, 2021 BASE Show details 4 On Homophony and Rényi Entropy ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Cotterell, Ryan; Meister, Clara. - : Underline Science Inc., 2021 BASE Show details 5 Searching for Search Errors in Neural Morphological Inflection ... Forster, Martina; Meister, Clara Isabel; Cotterell, Ryan. - : ETH Zurich, 2021 BASE Show details 6 Revisiting the Uniform Information Density Hypothesis ... Meister, Clara; Pimentel, Tiago; Haller, Patrick. - : arXiv, 2021 BASE Show details 7 Revisiting the Uniform Information Density Hypothesis ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Cotterell, Ryan; Haller, Patrick. - : Underline Science Inc., 2021 BASE Show details 8 Conditional Poisson Stochastic Beams ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Amini, Afra; Cotterell, Ryan. - : Underline Science Inc., 2021 BASE Show details 9 Language Model Evaluation Beyond Perplexity ... 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 10 A surprisal--duration trade-off across and within the world's languages ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Blasi, Damián; Cotterell, Ryan. - : Underline Science Inc., 2021 BASE Show details 11 Determinantal Beam Search ... 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; Forster, Martina. - : Underline Science Inc., 2021 BASE Show details 12 Is Sparse Attention more Interpretable? ... 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; Augenstein, Isabelle; Cotterell, Ryan. - : Underline Science Inc., 2021 BASE Show details 13 Revisiting the Uniform Information Density Hypothesis ... Meister, Clara Isabel; Pimentel, Tiago; Haller, Patrick. - : ETH Zurich, 2021 BASE Show details 14 A Plug-and-Play Method for Controlled Text Generation ... Pascual, Damian; Egressy, Béni; Meister, Clara Isabel. - : ETH Zurich, 2021 BASE Show details 15 Language Model Evaluation Beyond Perplexity ... Meister, Clara Isabel; Cotterell, Ryan. - : ETH Zurich, 2021 BASE Show details 16 Determinantal Beam Search ... Meister, Clara Isabel; Forster, Martina; Cotterell, Ryan. - : ETH Zurich, 2021 BASE Show details 17 Is Sparse Attention more Interpretable? ... Meister, Clara Isabel; Lazov, Stefan; Augenstein, Isabelle; Cotterell, Ryan. - : ETH Zurich, 2021 Abstract: Sparse attention has been claimed to increase model interpretability under the assumption that it highlights influential inputs. Yet the attention distribution is typically over representations internal to the model rather than the inputs themselves, suggesting this assumption may not have merit. We build on the recent work exploring the interpretability of attention; we design a set of experiments to help us understand how sparsity affects our ability to use attention as an explainability tool. On three text classification tasks, we verify that only a weak relationship between inputs and co-indexed intermediate representations exists-under sparse attention and otherwise. Further, we do not find any plausible mappings from sparse attention distributions to a sparse set of influential inputs through other avenues. Rather, we observe in this setting that inducing sparsity may make it less plausible that attention can be used as a tool for understanding model behavior. ... : Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing ... URL: https://dx.doi.org/10.3929/ethz-b-000507680 http://hdl.handle.net/20.500.11850/507680 BASE Hide details 18 A Cognitive Regularizer for Language Modeling ... Wei, Jason; Meister, Clara; Cotterell, Ryan. - : arXiv, 2021 BASE Show details 19 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 20 A Cognitive Regularizer for Language Modeling ... Wei, Jason; Meister, Clara Isabel; Cotterell, Ryan. - : ETH Zurich, 2021 BASE Show details Page: 1 2

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