Luke Zettlemoyer
Title
Cited by
Cited by
Year
Deep contextualized word representations
ME Peters, M Neumann, M Iyyer, M Gardner, C Clark, K Lee, ...
arXiv preprint arXiv:1802.05365, 2018
25912018
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
681*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
6402011
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
3532007
Learning to parse natural language commands to a robot control system
C Matuszek, E Herbst, L Zettlemoyer, D Fox
Experimental robotics, 403-415, 2013
3102013
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
2982013
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
2922014
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
2692010
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
2662017
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
2662013
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
2572013
Roberta: A robustly optimized bert pretraining approach
Y Liu, M Ott, N Goyal, J Du, M Joshi, D Chen, O Levy, M Lewis, ...
arXiv preprint arXiv:1907.11692, 2019
255*2019
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
2492012
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
2282018
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
2182009
Lifted Probabilistic Inference with Counting Formulas.
B Milch, LS Zettlemoyer, K Kersting, M Haimes, LP Kaelbling
Aaai 8, 1062-1068, 2008
2132008
End-to-end neural coreference resolution
K Lee, L He, M Lewis, L Zettlemoyer
arXiv preprint arXiv:1707.07045, 2017
2112017
Learning symbolic models of stochastic domains
HM Pasula, LS Zettlemoyer, LP Kaelbling
Journal of Artificial Intelligence Research 29, 309-352, 2007
2042007
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
1992017
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
1792011
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