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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 (2)
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Hits 1 – 10 of 10
1
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
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2
On Finding the K-best Non-projective Dependency Trees ...
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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3
On Finding the K-best Non-projective Dependency Trees ...
Zmigrod, Ran
;
Vieira, Tim
;
Cotterell, Ryan
. - : ETH Zurich, 2021
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4
Efficient computation of expectations under spanning tree distributions ...
Zmigrod, Ran
;
Vieira, Tim
;
Cotterell, Ryan
. - : ETH Zurich, 2021
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5
Higher-order Derivatives of Weighted Finite-state Machines ...
Zmigrod, Ran
;
Vieira, Tim
;
Cotterell, Ryan
. - : ETH Zurich, 2021
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6
On Finding the K-best Non-projective Dependency Trees
Zmigrod, Ran
;
Cotterell, Ryan
;
Vieira, Tim
In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (2021)
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7
Higher-order Derivatives of Weighted Finite-state Machines
Zmigrod, Ran
;
Cotterell, Ryan
;
Vieira, Tim
In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (2021)
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8
Efficient computation of expectations under spanning tree distributions
Cotterell, Ryan
;
Zmigrod, Ran
;
Vieira, Tim
In: Transactions of the Association for Computational Linguistics, 9 (2021)
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9
Efficient Sampling of Dependency Structure
Vieira, Tim
;
Zmigrod, Ran
;
Cotterell, Ryan
In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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10
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)
Abstract:
The connection between dependency trees and spanning trees is exploited by the NLP community to train and to decode graph-based dependency parsers. However, the NLP literature has missed an important difference between the two structures: only one edge may emanate from the root in a dependency tree. We analyzed the output of state-of-the-art parsers on many languages from the Universal Dependency Treebank: although these parsers are often able to learn that trees which violate the constraint should be assigned lower probabilities, their ability to do so unsurprisingly de-grades as the size of the training set decreases.In fact, the worst constraint-violation rate we observe is 24%. Prior work has proposed an inefficient algorithm to enforce the constraint, which adds a factor of n to the decoding runtime. We adapt an algorithm due to Gabow and Tarjan (1984) to dependency parsing, which satisfies the constraint without compromising the original runtime.
URL:
https://doi.org/10.3929/ethz-b-000462321
https://hdl.handle.net/20.500.11850/462321
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