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Cotterell, Ryan (75)
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The 2021 Conference on Empirical Methods in Natural Language Processing 2021 (8)
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 (8)
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Hits 1 – 20 of 75
1
On Homophony and Rényi Entropy ...
Pimentel, Tiago
;
Meister, Clara Isabel
;
Teufel, Simone
. - : ETH Zurich, 2021
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2
On Homophony and Rényi Entropy ...
Pimentel, Tiago
;
Meister, Clara
;
Teufel, Simone
. - : arXiv, 2021
BASE
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3
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
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4
Towards Zero-shot Language Modeling ...
Ponti, Edoardo Maria
;
Vulić, Ivan
;
Cotterell, Ryan
. - : arXiv, 2021
BASE
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5
Differentiable Generative Phonology ...
Wu, Shijie
;
Ponti, Edoardo Maria
;
Cotterell, Ryan
. - : arXiv, 2021
BASE
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6
Finding Concept-specific Biases in Form--Meaning Associations ...
Pimentel, Tiago
;
Roark, Brian
;
Wichmann, Søren
. - : arXiv, 2021
BASE
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7
Searching for Search Errors in Neural Morphological Inflection ...
Forster, Martina
;
Meister, Clara Isabel
;
Cotterell, Ryan
. - : ETH Zurich, 2021
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8
Applying the Transformer to Character-level Transduction ...
Wu, Shijie
;
Cotterell, Ryan
;
Hulden, Mans
. - : ETH Zurich, 2021
Abstract:
The transformer has been shown to outperform recurrent neural network-based sequence-to-sequence models in various word-level NLP tasks. Yet for character-level transduction tasks, e.g. morphological inflection generation and historical text normalization, there are few works that outperform recurrent models using the transformer. In an empirical study, we uncover that, in contrast to recurrent sequence-to-sequence models, the batch size plays a crucial role in the performance of the transformer on character-level tasks, and we show that with a large enough batch size, the transformer does indeed outperform recurrent models. We also introduce a simple technique to handle feature-guided character-level transduction that further improves performance. With these insights, we achieve state-of-the-art performance on morphological inflection and historical text normalization. We also show that the transformer outperforms a strong baseline on two other character-level transduction tasks: grapheme-to-phoneme ... : Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume ...
URL:
https://dx.doi.org/10.3929/ethz-b-000518998
http://hdl.handle.net/20.500.11850/518998
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9
Quantifying Gender Bias Towards Politicians in Cross-Lingual Language Models ...
Stańczak, Karolina
;
Choudhury, Sagnik Ray
;
Pimentel, Tiago
. - : arXiv, 2021
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10
Probing as Quantifying Inductive Bias ...
Immer, Alexander
;
Hennigen, Lucas Torroba
;
Fortuin, Vincent
. - : arXiv, 2021
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11
Revisiting the Uniform Information Density Hypothesis ...
Meister, Clara
;
Pimentel, Tiago
;
Haller, Patrick
. - : arXiv, 2021
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12
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
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13
Conditional Poisson Stochastic Beams ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Amini, Afra
;
Cotterell, Ryan
. - : Underline Science Inc., 2021
BASE
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14
Examining the Inductive Bias of Neural Language Models with Artificial Languages ...
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
;
White, Jennifer
. - : Underline Science Inc., 2021
BASE
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15
Modeling the Unigram Distribution ...
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
;
Blasi, Damián
;
Cotterell, Ryan
. - : Underline Science Inc., 2021
BASE
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16
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
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17
Differentiable Subset Pruning of Transformer Heads ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Cotterell, Ryan
;
Li, Jiaoda
. - : Underline Science Inc., 2021
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18
A Bayesian Framework for Information-Theoretic Probing ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Cotterell, Ryan
;
Pimentel, Tiago
. - : Underline Science Inc., 2021
BASE
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19
Classifying Dyads for Militarized Conflict Analysis ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Ahbab, Samin
;
Cotterell, Ryan
. - : Underline Science Inc., 2021
BASE
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20
Higher-order Derivatives of Weighted Finite-state Machines ...
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
;
Vieira, Tim
. - : Underline Science Inc., 2021
BASE
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