Roy Schwartz - Google Scholar Citations

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Co-authors

Noah A. SmithUniversity of Washington; Allen Institute for Artificial IntelligenceVerified email at cs.washington.edu
Ari RappoportAssociate Professor of Computer Science, The Hebrew UniversityVerified email at mail.huji.ac.il
Roi ReichartTechnion - Israel Institute of TechnologyVerified email at ie.technion.ac.il
Yejin ChoiUniversity of Washington / Allen Institute for Artificial IntelligenceVerified email at cs.washington.edu
Suchin GururanganAllen Institute for AIVerified email at allenai.org
Omer LevyTel Aviv UniversityVerified email at cs.tau.ac.il
Swabha SwayamdiptaAllen Institute of Artificial IntelligenceVerified email at allenai.org
Omri AbendFaculty member, Hebrew University of JerusalemVerified email at mail.huji.ac.il
Jesse DodgeCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Samuel R. BowmanAssistant Professor, NYUVerified email at nyu.edu
Rowan ZellersPh.D. Student, University of WashingtonVerified email at cs.washington.edu
Yonatan BiskCarnegie Mellon UniversityVerified email at cs.cmu.edu
Maarten SapUniversity of WashingtonVerified email at cs.washington.edu
Ioannis KonstasHeriot-Watt UniversityVerified email at hw.ac.uk
Moshe KoppelBar-Ilan UniversityVerified email at cs.biu.ac.il
Oren TsurBen Gurion UniversityVerified email at bgu.ac.il
Nelson F. LiuStanford UniversityVerified email at cs.stanford.edu
Dongyeop KangCarnegie Mellon UniversityVerified email at cs.cmu.edu
Waleed AmmarGoogleVerified email at allenai.org
Eduard HovyCarnegie Mellon UniversityVerified email at cmu.edu

Roy Schwartz

Research Scientist, Allen Institute for Artificial Intelligence, University of Washington

Verified email at allenai.org - Homepage

Computational Linguistics Natural Language Processing Artificial Intelligence Machine Learning


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Annotation Artifacts in Natural Language Inference Data S Gururangan, S Swayamdipta, O Levy, R Schwartz, SR Bowman, ... NAACL-HLT 2018, 2018	171	2018
SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference R Zellers, Y Bisk, R Schwartz, Y Choi EMNLP 2018, 2018	115	2018
Authorship Attribution of Micro-Messages R Schwartz, O Tsur, A Rappoport, M Koppel EMNLP 2013, 2013	100	2013
Symmetric Pattern Based Word Embeddings for Improved Word Similarity Prediction. R Schwartz, R Reichart, A Rappoport CoNLL 2015, 2015	85	2015
Learnability-Based Syntactic Annotation Design. R Schwartz, O Abend, A Rappoport COLING 2012, 2012	51	2012
Neutralizing linguistically problematic annotations in unsupervised dependency parsing evaluation R Schwartz, O Abend, R Reichart, A Rappoport ACL 2011, 2011	41	2011
How well do distributional models capture different types of semantic knowledge? D Rubinstein, E Levi, R Schwartz, A Rappoport ACL 2015, 2015	40	2015
Green AI R Schwartz, J Dodge, NA Smith, O Etzioni arXiv preprint arXiv:1907.10597, 2019	37*	2019
The Effect of Different Writing Tasks on Linguistic Style: A Case Study of the ROC Story Cloze Task R Schwartz, M Sap, I Konstas, L Zilles, Y Choi, NA Smith CoNLL 2017, 2017	31	2017
A Dataset of Peer Reviews (PeerRead): Collection, Insights and NLP Applications D Kang, W Ammar, B Dalvi, M van Zuylen, S Kohlmeier, E Hovy, ... NAACL 2018, 2018	26	2018
Story Cloze Task: UW NLP System R Schwartz, M Sap, I Konstas, L Zilles, Y Choi, NA Smith LSDSem 2017, 2017	19	2017
Inoculation by Fine-Tuning: A Method for Analyzing Challenge Datasets NF Liu, R Schwartz, NA Smith NAACL 2019, 2019	18	2019
Symmetric Patterns and Coordinations: Fast and Enhanced Representations of Verbs and Adjectives. R Schwartz, R Reichart, A Rappoport NAACL 2016, 2016	16	2016
Show Your Work: Improved Reporting of Experimental Results J Dodge, S Gururangan, D Card, R Schwartz, NA Smith EMNLP 2019, 2019	15	2019
Rational Recurrences H Peng, R Schwartz, S Thomson, NA Smith EMNLP 2018, 2018	15	2018
Knowledge Enhanced Contextual Word Representations ME Peters, M Neumann, RL Logan IV, R Schwartz, V Joshi, S Singh, ... EMNLP 2019, 2019	12	2019
Automatic selection of context configurations for improved (and fast) class-specific word representations I Vulić, R Schwartz, A Rappoport, R Reichart, A Korhonen CoNLL 2017, 2016	11*	2016
LSTMs Exploit Linguistic Attributes of Data NF Liu, O Levy, R Schwartz, C Tan, NA Smith RepL4NLP 2018, 2018	10	2018
SoPa: Bridging CNNs, RNNs, and weighted finite-state machines R Schwartz, S Thomson, NA Smith ACL 2018, 2018	10*	2018
Minimally Supervised Classification to Semantic Categories using Automatically Acquired Symmetric Patterns. R Schwartz, R Reichart, A Rappoport COLING 2014, 2014	6	2014

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