Roy Schwartz

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Noah A. SmithUniversity of Washington; Allen Institute for Artificial IntelligenceE-mail confirmado em cs.washington.edu
Jesse DodgeAllen Institute for AIE-mail confirmado em allenai.org
Yejin ChoiStanford University / NVIDIAE-mail confirmado em stanford.edu
Ari RappoportAssociate Professor of Computer Science, The Hebrew UniversityE-mail confirmado em mail.huji.ac.il
Hannaneh HajishirziUniversity of Washington; Allen AIE-mail confirmado em cs.washington.edu
Hao PengUniversity of Illinois Urbana-ChampaignE-mail confirmado em illinois.edu
Swabha SwayamdiptaUniversity of Southern CaliforniaE-mail confirmado em usc.edu
Suchin GururanganUniversity of WashingtonE-mail confirmado em cs.washington.edu
Gabriel StanovskyThe Hebrew University of JerusalemE-mail confirmado em mail.huji.ac.il
Omer LevyGoogle DeepMindE-mail confirmado em google.com
Michael HassidMeta FAIR, Hebrew University of JerusalemE-mail confirmado em mail.huji.ac.il
Oren EtzioniUniversity of WashingtonE-mail confirmado em etzioni.ai
Nikolaos PappasAmazon (AWS AI Labs)E-mail confirmado em amazon.com
Matthew E PetersSpiffy AI, Allen Institute for Artificial IntelligenceE-mail confirmado em allenai.org
Emma StrubellAssistant Professor, Carnegie Mellon UniversityE-mail confirmado em cs.cmu.edu
Roi ReichartTechnion - Israel Institute of TechnologyE-mail confirmado em technion.ac.il
Yonatan BittonResearch Scientist, GoogleE-mail confirmado em google.com
Vidur JoshiAllen Institute for Artificial IntelligenceE-mail confirmado em allenai.org
Sameer SinghProfessor, UC Irvine | CTO, Spiffy AIE-mail confirmado em uci.edu
Yonatan BiskAssistant Professor, Carnegie Mellon UniversityE-mail confirmado em cs.cmu.edu

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Roy Schwartz

Associate Professor, the School of Computer Science, the Hebrew University of Jerusalem

E-mail confirmado em mail.huji.ac.il - Página inicial

Natural Language Processing Artificial Intelligence Machine Learning


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
Green AI R Schwartz, J Dodge, NA Smith, O Etzioni CACM 63 (December 2020), 54-63, 2020	1787*	2020
Annotation Artifacts in Natural Language Inference Data S Gururangan, S Swayamdipta, O Levy, R Schwartz, SR Bowman, ... NAACL-HLT 2018, 2018	1294	2018
Knowledge Enhanced Contextual Word Representations ME Peters, M Neumann, RL Logan IV, R Schwartz, V Joshi, S Singh, ... EMNLP 2019, 2019	869	2019
SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference R Zellers, Y Bisk, R Schwartz, Y Choi EMNLP 2018, 2018	866	2018
Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping J Dodge, G Ilharco, R Schwartz, A Farhadi, H Hajishirzi, N Smith arXiv:2002.06305, 2020	708	2020
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics S Swayamdipta, R Schwartz, N Lourie, Y Wang, H Hajishirzi, NA Smith, ... EMNLP 2020, 2020	428	2020
Random Feature Attention H Peng, N Pappas, D Yogatama, R Schwartz, NA Smith, L Kong ICLR 2021, 2021	380	2021
Show Your Work: Improved Reporting of Experimental Results J Dodge, S Gururangan, D Card, R Schwartz, NA Smith EMNLP 2019, 2019	301	2019
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	236	2018
Measuring the Carbon Intensity of AI in Cloud Instances J Dodge, T Prewitt, RTD Combes, E Odmark, R Schwartz, E Strubell, ... FAccT 2022, 2022	205	2022
Authorship Attribution of Micro-Messages R Schwartz, O Tsur, A Rappoport, M Koppel EMNLP 2013, 2013	196	2013
The Right Tool for the Job: Matching Model and Instance Complexities R Schwartz, G Stanovsky, S Swayamdipta, J Dodge, NA Smith ACL 2020, 2020	175	2020
Data Contamination: From Memorization to Exploitation I Magar, R Schwartz ACL 2022, 2022	167	2022
Symmetric Pattern Based Word Embeddings for Improved Word Similarity Prediction. R Schwartz, R Reichart, A Rappoport CoNLL 2015, 2015	144	2015
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	129	2017
Inoculation by Fine-Tuning: A Method for Analyzing Challenge Datasets NF Liu, R Schwartz, NA Smith NAACL 2019, 2019	121	2019
Efficient Methods for Natural Language Processing: A Survey M Treviso, T Ji, JU Lee, B van Aken, Q Cao, MR Ciosici, M Hassid, ... TACL, 2023	116	2023
How well do distributional models capture different types of semantic knowledge? D Rubinstein, E Levi, R Schwartz, A Rappoport ACL 2015, 2015	92	2015
A Formal Hierarchy of RNN Architectures W Merrill, G Weiss, Y Goldberg, R Schwartz, NA Smith, E Yahav ACL 2020, 2020	87	2020
Provable Limitations of Acquiring Meaning from Ungrounded Form: What will Future Language Models Understand? W Merrill, Y Goldberg, R Schwartz, NA Smith TACL, 2021	74	2021

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