Luke Zettlemoyer
Luke Zettlemoyer
Bestätigte E-Mail-Adresse bei cs.washington.edu - Startseite
TitelZitiert vonJahr
Deep contextualized word representations
ME Peters, M Neumann, M Iyyer, M Gardner, C Clark, K Lee, ...
arXiv preprint arXiv:1802.05365, 2018
14572018
Learning to map sentences to logical form: Structured classification with probabilistic categorial grammars
LS Zettlemoyer, M Collins
Conference on Uncertainty in Artificial Intelligence (UAI), 2005
630*2005
Knowledge-based weak supervision for information extraction of overlapping relations
R Hoffmann, C Zhang, X Ling, L Zettlemoyer, DS Weld
Proceedings of the 49th Annual Meeting of the Association for Computational …, 2011
5542011
Online learning of relaxed CCG grammars for parsing to logical form
L Zettlemoyer, M Collins
Proceedings of the 2007 Joint Conference on Empirical Methods in Natural …, 2007
3302007
Learning to parse natural language commands to a robot control system
C Matuszek, E Herbst, L Zettlemoyer, D Fox
Experimental Robotics, 403-415, 2013
2872013
Weakly supervised learning of semantic parsers for mapping instructions to actions
Y Artzi, L Zettlemoyer
Transactions of the Association for Computational Linguistics 1, 49-62, 2013
2662013
Open question answering over curated and extracted knowledge bases
A Fader, L Zettlemoyer, O Etzioni
Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014
2582014
Inducing probabilistic CCG grammars from logical form with higher-order unification
T Kwiatkowski, L Zettlemoyer, S Goldwater, M Steedman
Proceedings of the 2010 conference on empirical methods in natural language …, 2010
2572010
Scaling semantic parsers with on-the-fly ontology matching
T Kwiatkowski, E Choi, Y Artzi, L Zettlemoyer
Proceedings of the 2013 conference on empirical methods in natural language …, 2013
2382013
Paraphrase-driven learning for open question answering
A Fader, L Zettlemoyer, O Etzioni
Proceedings of the 51st Annual Meeting of the Association for Computational …, 2013
2312013
A joint model of language and perception for grounded attribute learning
C Matuszek, N FitzGerald, L Zettlemoyer, L Bo, D Fox
arXiv preprint arXiv:1206.6423, 2012
2222012
Lifted Probabilistic Inference with Counting Formulas.
B Milch, LS Zettlemoyer, K Kersting, M Haimes, LP Kaelbling
Aaai 8, 1062-1068, 2008
2112008
Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension
M Joshi, E Choi, DS Weld, L Zettlemoyer
arXiv preprint arXiv:1705.03551, 2017
2022017
Reinforcement learning for mapping instructions to actions
SRK Branavan, H Chen, LS Zettlemoyer, R Barzilay
Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL …, 2009
2022009
Learning symbolic models of stochastic domains
HM Pasula, LS Zettlemoyer, LP Kaelbling
Journal of Artificial Intelligence Research 29, 309-352, 2007
1972007
Lexical generalization in CCG grammar induction for semantic parsing
T Kwiatkowski, L Zettlemoyer, S Goldwater, M Steedman
Proceedings of the conference on empirical methods in natural language …, 2011
1642011
Learning context-dependent mappings from sentences to logical form
LS Zettlemoyer, M Collins
Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL …, 2009
1612009
End-to-end neural coreference resolution
K Lee, L He, M Lewis, L Zettlemoyer
arXiv preprint arXiv:1707.07045, 2017
1512017
Towards narrative-centered learning environments
BW Mott, CB Callaway, LS Zettlemoyer, SY Lee, JC Lester
Proceedings of the 1999 AAAI fall symposium on narrative intelligence, 78-82, 1999
1491999
Deep semantic role labeling: What works and what’s next
L He, K Lee, M Lewis, L Zettlemoyer
Proceedings of the 55th Annual Meeting of the Association for Computational …, 2017
1462017
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