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Cotterell, Ryan (22)
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The 2021 Conference on Empirical Methods in Natural Language Processing 2021 (4)
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 (4)
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Hits 1 – 20 of 22
1
Estimating the Entropy of Linguistic Distributions ...
Arora, Aryaman
;
Meister, Clara
;
Cotterell, Ryan
. - : arXiv, 2022
BASE
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2
On Homophony and Rényi Entropy ...
Pimentel, Tiago
;
Meister, Clara Isabel
;
Teufel, Simone
. - : ETH Zurich, 2021
BASE
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3
On Homophony and Rényi Entropy ...
Pimentel, Tiago
;
Meister, Clara
;
Teufel, Simone
. - : arXiv, 2021
BASE
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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
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5
Searching for Search Errors in Neural Morphological Inflection ...
Forster, Martina
;
Meister, Clara Isabel
;
Cotterell, Ryan
. - : ETH Zurich, 2021
BASE
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6
Revisiting the Uniform Information Density Hypothesis ...
Meister, Clara
;
Pimentel, Tiago
;
Haller, Patrick
. - : arXiv, 2021
BASE
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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
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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
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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
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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
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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
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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
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13
Revisiting the Uniform Information Density Hypothesis ...
Meister, Clara Isabel
;
Pimentel, Tiago
;
Haller, Patrick
. - : ETH Zurich, 2021
BASE
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14
A Plug-and-Play Method for Controlled Text Generation ...
Pascual, Damian
;
Egressy, Béni
;
Meister, Clara Isabel
. - : ETH Zurich, 2021
BASE
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15
Language Model Evaluation Beyond Perplexity ...
Meister, Clara Isabel
;
Cotterell, Ryan
. - : ETH Zurich, 2021
BASE
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16
Determinantal Beam Search ...
Meister, Clara Isabel
;
Forster, Martina
;
Cotterell, Ryan
. - : ETH Zurich, 2021
BASE
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17
Is Sparse Attention more Interpretable? ...
Meister, Clara Isabel
;
Lazov, Stefan
;
Augenstein, Isabelle
. - : ETH Zurich, 2021
BASE
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18
A Cognitive Regularizer for Language Modeling ...
Wei, Jason
;
Meister, Clara
;
Cotterell, Ryan
. - : arXiv, 2021
Abstract:
The uniform information density (UID) hypothesis, which posits that speakers behaving optimally tend to distribute information uniformly across a linguistic signal, has gained traction in psycholinguistics as an explanation for certain syntactic, morphological, and prosodic choices. In this work, we explore whether the UID hypothesis can be operationalized as an inductive bias for statistical language modeling. Specifically, we augment the canonical MLE objective for training language models with a regularizer that encodes UID. In experiments on ten languages spanning five language families, we find that using UID regularization consistently improves perplexity in language models, having a larger effect when training data is limited. Moreover, via an analysis of generated sequences, we find that UID-regularized language models have other desirable properties, e.g., they generate text that is more lexically diverse. Our results not only suggest that UID is a reasonable inductive bias for language modeling, ... : ACL 2021 Camera-ready (fixed ordering of affiliation emojis) ...
Keyword:
Computation and Language cs.CL
;
FOS Computer and information sciences
URL:
https://dx.doi.org/10.48550/arxiv.2105.07144
https://arxiv.org/abs/2105.07144
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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
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20
A Cognitive Regularizer for Language Modeling ...
Wei, Jason
;
Meister, Clara Isabel
;
Cotterell, Ryan
. - : ETH Zurich, 2021
BASE
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