Gabriel Stanovsky

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Citations	2483	2416
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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
Noah A. SmithUniversity of Washington; Allen Institute for Artificial IntelligenceVerified email at cs.washington.edu
Roy SchwartzSenior lecturer, the School of Computer Science, the Hebrew University of JerusalemVerified email at mail.huji.ac.il
Matt GardnerScaled CognitionVerified email at scaledcognition.com
Sameer SinghAssociate Professor, University of California IrvineVerified email at uci.edu
Julian MichaelNew York UniversityVerified email at nyu.edu
Iryna GurevychFull Professor, TU Darmstadt; Adjunct Professor, MBZUAI, Abu DhabiVerified 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
Yonatan BittonResearch Scientist, GoogleVerified email at google.com
Arie CattanBar-Ilan UniversityVerified email at biu.ac.il
Jonathan BraggAllen Institute for AI (AI2)Verified email at allenai.org
Daniel KhashabiJohns Hopkins UniversityVerified email at jhu.edu
Jungo KasaiToyota Technological Institute at Chicago, Kotoba Technologies, Inc.Verified email at ttic.edu
Mandar JoshiGoogle AIVerified email at google.com
Alon EirewBar Ilan UniversityVerified email at live.biu.ac.il
Tomasz LimisiewiczPh.D. Candidate, Institute of Formal and Applied Linguistics, Charles University, Prague, CzechVerified email at ufal.mff.cuni.cz
Anthony ChenGoogle DeepMindVerified email at google.com

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	596	2019
Evaluating gender bias in machine translation G Stanovsky, NA Smith, L Zettlemoyer arXiv preprint arXiv:1906.00591, 2019	319	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	300	2018
Creating a large benchmark for open information extraction G Stanovsky, I Dagan Proceedings of the 2016 Conference on Empirical Methods in Natural Language …, 2016	144	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	112	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	78	2015
Open IE as an Intermediate Structure for Semantic Tasks G Stanovsky, I Dagan, Mausam Association for Computational Linguistics, 303-308, 2015	78	2015
Crowdsourcing question-answer meaning representations J Michael, G Stanovsky, L He, I Dagan, L Zettlemoyer arXiv preprint arXiv:1711.05885, 2017	76	2017
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	71	2017
Getting more out of syntax with props G Stanovsky, J Ficler, I Dagan, Y Goldberg arXiv preprint arXiv:1603.01648, 2016	65	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 preprint arXiv:2101.06561, 2021	63	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	55	2019
Gender trends in computer science authorship LL Wang, G Stanovsky, L Weihs, O Etzioni Communications of the ACM 64 (3), 78-84, 2021	52	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	51	2017
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	40	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	34	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	30	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	29	2019
Gender coreference and bias evaluation at wmt 2020 T Kocmi, T Limisiewicz, G Stanovsky arXiv preprint arXiv:2010.06018, 2020	28	2020
Collecting a large-scale gender bias dataset for coreference resolution and machine translation S Levy, K Lazar, G Stanovsky arXiv preprint arXiv:2109.03858, 2021	27	2021

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