Tim Vieira
Title
Cited by
Cited by
Year
Universal Decompositional Semantics on Universal Dependencies
AS White, D Reisinger, K Sakaguchi, T Vieira, S Zhang, R Rudinger, ...
Empirical Methods in Natural Language Processing, 2016
1012016
Reasoning about quantities in natural language
S Roy, T Vieira, D Roth
Transactions of the Association for Computational Linguistics 3, 1-13, 2015
882015
Relation Alignment for Textual Entailment Recognition.
M Sammons, VGV Vydiswaran, T Vieira, N Johri, MW Chang, ...
TAC, 2009
522009
A Joint Model of Orthography and Morphological Segmentation
R Cotterell, T Vieira, H Schütze
NAACL, 2016
362016
If beam search is the answer, what was the question?
C Meister, T Vieira, R Cotterell
arXiv preprint arXiv:2010.02650, 2020
212020
Best-first beam search
C Meister, T Vieira, R Cotterell
Transactions of the Association for Computational Linguistics 8, 795-809, 2020
112020
Learning to prune: Exploring the frontier of fast and accurate parsing
T Vieira, J Eisner
Transactions of the Association for Computational Linguistics 5, 263-278, 2017
102017
Grammarless parsing for joint inference
J Naradowsky, T Vieira, DA Smith
Proceedings of COLING 2012, 1995-2010, 2012
92012
Speed-accuracy tradeoffs in tagging with variable-order CRFs and structured sparsity
T Vieira, R Cotterell, J Eisner
Proceedings of the 2016 Conference on Empirical Methods in Natural Language …, 2016
82016
The universal decompositional semantics dataset and decomp toolkit
AS White, E Stengel-Eskin, S Vashishtha, V Govindarajan, DA Reisinger, ...
arXiv preprint arXiv:1909.13851, 2019
72019
Gumbel-max trick and weighted reservoir sampling, 2014
T Vieira
URL https://timvieira. github. io/blog/post/2014/08/01/gumbel-max-trick …, 0
7
Dyna: Toward a self-optimizing declarative language for machine learning applications
T Vieira, M Francis-Landau, NW Filardo, F Khorasani, J Eisner
Proceedings of the 1st ACM SIGPLAN International Workshop on Machine …, 2017
52017
Estimating means in a finite universe, 2017
T Vieira
URL https://timvieira. github. io/blog/post/2017/07/03/estimating-means-in-a …, 2017
52017
Please mind the root: Decoding arborescences for dependency parsing
R Zmigrod, T Vieira, R Cotterell
arXiv preprint arXiv:2010.02550, 2020
42020
Gumbel-max trick and weighted reservoir sampling
T Vieira
32014
Efficient computation of expectations under spanning tree distributions
R Zmigrod, T Vieira, R Cotterell
Transactions of the Association for Computational Linguistics 9, 675-690, 2021
22021
Exp-normalize trick
T Vieira
2
Searching for More Efficient Dynamic Programs
T Vieira, R Cotterell, J Eisner
arXiv preprint arXiv:2109.06966, 2021
2021
Efficient Sampling of Dependency Structures
R Zmigrod, T Vieira, R Cotterell
arXiv preprint arXiv:2109.06521, 2021
2021
On Finding the -best Non-projective Dependency Trees
R Zmigrod, T Vieira, R Cotterell
arXiv preprint arXiv:2106.00780, 2021
2021
The system can't perform the operation now. Try again later.
Articles 1–20