Gabriel Stanovsky

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Ido DaganProfessor, Computer Science Department, Bar-Ilan UniversityVerified email at cs.biu.ac.il
Luke ZettlemoyerUniversity of Washington; Meta AIVerified email at cs.washington.edu
Matt GardnerMicrosoft Semantic MachinesVerified email at microsoft.com
Sameer SinghAssociate Professor, University of California IrvineVerified email at uci.edu
Noah A. SmithUniversity of Washington; Allen Institute for Artificial IntelligenceVerified email at cs.washington.edu
Julian MichaelUniversity of WashingtonVerified email at cs.washington.edu
Roy SchwartzSenior lecturer, the School of Computer Science, the Hebrew University of JerusalemVerified email at mail.huji.ac.il
Iryna GurevychProfessor of Computer Science, Technische Universität DarmstadtVerified email at cs.tu-darmstadt.de
Dheeru DuaUniversity of California, IrvineVerified email at uci.edu
Pradeep DasigiAllen Institute for AI (AI2)Verified email at allenai.org
Yizhong WangUniversity of WashingtonVerified email at cs.washington.edu
Mandar JoshiGoogle AIVerified email at google.com
Alon EirewBar Ilan University & Intel LabsVerified email at live.biu.ac.il
Arie CattanBar-Ilan UniversityVerified email at biu.ac.il
Yonatan BittonResearcherVerified email at cs.huji.ac.il
Anthony ChenUniversity of California, IrvineVerified email at uci.edu
Yoav GoldbergProfessor, Bar Ilan UniversityVerified email at cs.biu.ac.il
Judith Eckle-KohlerVerified email at eckle-kohler.de
Yejin ChoiUniversity of Washington / Allen Institute for Artificial IntelligenceVerified email at cs.washington.edu
Jonathan BraggAllen Institute for AI (AI2)Verified email at allenai.org

Gabriel Stanovsky

The Hebrew University of Jerusalem

Verified email at mail.huji.ac.il - Homepage

Computational Linguistics


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DROP: A reading comprehension benchmark requiring discrete reasoning over paragraphs D Dua, Y Wang, P Dasigi, G Stanovsky, S Singh, M Gardner arXiv preprint arXiv:1903.00161, 2019	486	2019
Supervised open information extraction G Stanovsky, J Michael, L Zettlemoyer, I Dagan Proceedings of the 2018 Conference of the North American Chapter of the …, 2018	259	2018
Evaluating gender bias in machine translation G Stanovsky, NA Smith, L Zettlemoyer arXiv preprint arXiv:1906.00591, 2019	233	2019
Creating a large benchmark for open information extraction G Stanovsky, I Dagan Proceedings of the 2016 Conference on Empirical Methods in Natural Language …, 2016	128	2016
The right tool for the job: Matching model and instance complexities R Schwartz, G Stanovsky, S Swayamdipta, J Dodge, NA Smith arXiv preprint arXiv:2004.07453, 2020	74	2020
Open ie as an intermediate structure for semantic tasks G Stanovsky, I Dagan Proceedings of the 53rd Annual Meeting of the Association for Computational …, 2015	72	2015
Open IE as an Intermediate Structure for Semantic Tasks G Stanovsky, I Dagan, Mausam Association for Computational Linguistics, 303-308, 2015	72	2015
Recognizing mentions of adverse drug reaction in social media using knowledge-infused recurrent models G Stanovsky, D Gruhl, P Mendes Proceedings of the 15th Conference of the European Chapter of the …, 2017	64	2017
Crowdsourcing question-answer meaning representations J Michael, G Stanovsky, L He, I Dagan, L Zettlemoyer arXiv preprint arXiv:1711.05885, 2017	62	2017
Getting more out of syntax with props G Stanovsky, J Ficler, I Dagan, Y Goldberg arXiv preprint arXiv:1603.01648, 2016	58	2016
Genie: A leaderboard for human-in-the-loop evaluation of text generation D Khashabi, G Stanovsky, J Bragg, N Lourie, J Kasai, Y Choi, NA Smith, ... arXiv e-prints, arXiv: 2101.06561, 2021	48	2021
Integrating deep linguistic features in factuality prediction over unified datasets G Stanovsky, J Eckle-Kohler, Y Puzikov, I Dagan, I Gurevych Proceedings of the 55th Annual Meeting of the Association for Computational …, 2017	47	2017
Gender trends in computer science authorship LL Wang, G Stanovsky, L Weihs, O Etzioni Communications of the ACM 64 (3), 78-84, 2021	45	2021
Evaluating question answering evaluation A Chen, G Stanovsky, S Singh, M Gardner Proceedings of the 2nd workshop on machine reading for question answering …, 2019	45	2019
Controlled crowdsourcing for high-quality QA-SRL annotation P Roit, A Klein, D Stepanov, J Mamou, J Michael, G Stanovsky, ... arXiv preprint arXiv:1911.03243, 2019	32	2019
MOCHA: A dataset for training and evaluating generative reading comprehension metrics A Chen, G Stanovsky, S Singh, M Gardner arXiv preprint arXiv:2010.03636, 2020	26	2020
Streamlining cross-document coreference resolution: Evaluation and modeling A Cattan, A Eirew, G Stanovsky, M Joshi, I Dagan arXiv preprint arXiv:2009.11032, 2020	25	2020
Gender coreference and bias evaluation at wmt 2020 T Kocmi, T Limisiewicz, G Stanovsky arXiv preprint arXiv:2010.06018, 2020	23	2020
SemEval-2019 task 10: math question answering M Hopkins, R Le Bras, C Petrescu-Prahova, G Stanovsky, H Hajishirzi, ... Proceedings of the 13th International Workshop on Semantic Evaluation, 893-899, 2019	23	2019
Porting an open information extraction system from english to german T Falke, G Stanovsky, I Gurevych, I Dagan Proceedings of the 2016 Conference on Empirical Methods in Natural Language …, 2016	23	2016

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