Luke Zettlemoyer
TitleCited byYear
Deep contextualized word representations
ME Peters, M Neumann, M Iyyer, M Gardner, C Clark, K Lee, ...
arXiv preprint arXiv:1802.05365, 2018
19202018
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
652*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
5942011
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
3402007
Learning to parse natural language commands to a robot control system
C Matuszek, E Herbst, L Zettlemoyer, D Fox
Experimental Robotics, 403-415, 2013
2992013
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
2852013
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
2742014
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
2622010
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
2512013
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
2422013
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
2352017
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
2342012
Lifted Probabilistic Inference with Counting Formulas.
B Milch, LS Zettlemoyer, K Kersting, M Haimes, LP Kaelbling
Aaai 8, 1062-1068, 2008
2132008
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
2092009
Learning symbolic models of stochastic domains
HM Pasula, LS Zettlemoyer, LP Kaelbling
Journal of Artificial Intelligence Research 29, 309-352, 2007
2002007
End-to-end neural coreference resolution
K Lee, L He, M Lewis, L Zettlemoyer
arXiv preprint arXiv:1707.07045, 2017
1782017
Allennlp: A deep semantic natural language processing platform
M Gardner, J Grus, M Neumann, O Tafjord, P Dasigi, N Liu, M Peters, ...
arXiv preprint arXiv:1803.07640, 2018
1742018
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
1692011
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
1662017
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
1652009
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Articles 1–20