
Roy Schwartz 0001
Person information
- affiliation: The Hebrew University of Jerusalem, Israel
Other persons with the same name
- Roy Schwartz 0002 — Technion, Haifa, Israel
- Roy Schwartz 0003 — Microsoft Research, Redmond, WA, USA
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2020 – today
- 2020
- [j1]Roy Schwartz, Jesse Dodge, Noah A. Smith, Oren Etzioni:
Green AI. Commun. ACM 63(12): 54-63 (2020) - [c25]William Merrill, Gail Weiss, Yoav Goldberg, Roy Schwartz, Noah A. Smith, Eran Yahav
:
A Formal Hierarchy of RNN Architectures. ACL 2020: 443-459 - [c24]Hao Peng, Roy Schwartz, Dianqi Li, Noah A. Smith:
A Mixture of h - 1 Heads is Better than h Heads. ACL 2020: 6566-6577 - [c23]Roy Schwartz, Gabriel Stanovsky, Swabha Swayamdipta, Jesse Dodge, Noah A. Smith:
The Right Tool for the Job: Matching Model and Instance Complexities. ACL 2020: 6640-6651 - [c22]Swabha Swayamdipta, Roy Schwartz, Nicholas Lourie, Yizhong Wang, Hannaneh Hajishirzi, Noah A. Smith, Yejin Choi:
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics. EMNLP (1) 2020: 9275-9293 - [i21]Jesse Dodge, Gabriel Ilharco, Roy Schwartz, Ali Farhadi, Hannaneh Hajishirzi, Noah A. Smith:
Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping. CoRR abs/2002.06305 (2020) - [i20]Roy Schwartz, Gabi Stanovsky, Swabha Swayamdipta, Jesse Dodge, Noah A. Smith:
The Right Tool for the Job: Matching Model and Instance Complexities. CoRR abs/2004.07453 (2020) - [i19]William Merrill, Gail Weiss, Yoav Goldberg, Roy Schwartz, Noah A. Smith, Eran Yahav:
A Formal Hierarchy of RNN Architectures. CoRR abs/2004.08500 (2020) - [i18]Hao Peng, Roy Schwartz, Dianqi Li, Noah A. Smith:
A Mixture of h-1 Heads is Better than h Heads. CoRR abs/2005.06537 (2020) - [i17]Swabha Swayamdipta, Roy Schwartz, Nicholas Lourie, Yizhong Wang, Hannaneh Hajishirzi, Noah A. Smith, Yejin Choi:
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics. CoRR abs/2009.10795 (2020) - [i16]Aida Amini, Tom Hope, David Wadden, Madeleine van Zuylen, Eric Horvitz, Roy Schwartz, Hannaneh Hajishirzi:
Extracting a Knowledge Base of Mechanisms from COVID-19 Papers. CoRR abs/2010.03824 (2020) - [i15]William Merrill, Vivek Ramanujan, Yoav Goldberg, Roy Schwartz, Noah A. Smith:
Parameter Norm Growth During Training of Transformers. CoRR abs/2010.09697 (2020)
2010 – 2019
- 2019
- [c21]Matthew E. Peters, Mark Neumann, Robert L. Logan IV, Roy Schwartz, Vidur Joshi, Sameer Singh, Noah A. Smith:
Knowledge Enhanced Contextual Word Representations. EMNLP/IJCNLP (1) 2019: 43-54 - [c20]Jesse Dodge, Roy Schwartz, Hao Peng, Noah A. Smith:
RNN Architecture Learning with Sparse Regularization. EMNLP/IJCNLP (1) 2019: 1179-1184 - [c19]Jesse Dodge, Suchin Gururangan, Dallas Card, Roy Schwartz, Noah A. Smith:
Show Your Work: Improved Reporting of Experimental Results. EMNLP/IJCNLP (1) 2019: 2185-2194 - [c18]Hao Peng, Roy Schwartz, Noah A. Smith:
PaLM: A Hybrid Parser and Language Model. EMNLP/IJCNLP (1) 2019: 3642-3649 - [c17]Nelson F. Liu, Roy Schwartz, Noah A. Smith:
Inoculation by Fine-Tuning: A Method for Analyzing Challenge Datasets. NAACL-HLT (1) 2019: 2171-2179 - [i14]Nelson F. Liu, Roy Schwartz, Noah A. Smith:
Inoculation by Fine-Tuning: A Method for Analyzing Challenge Datasets. CoRR abs/1904.02668 (2019) - [i13]Roy Schwartz, Jesse Dodge, Noah A. Smith, Oren Etzioni:
Green AI. CoRR abs/1907.10597 (2019) - [i12]Hao Peng, Roy Schwartz, Noah A. Smith:
PaLM: A Hybrid Parser and Language Model. CoRR abs/1909.02134 (2019) - [i11]Jesse Dodge, Suchin Gururangan, Dallas Card, Roy Schwartz, Noah A. Smith:
Show Your Work: Improved Reporting of Experimental Results. CoRR abs/1909.03004 (2019) - [i10]Jesse Dodge, Roy Schwartz, Hao Peng, Noah A. Smith:
RNN Architecture Learning with Sparse Regularization. CoRR abs/1909.03011 (2019) - [i9]Matthew E. Peters, Mark Neumann, Robert L. Logan IV, Roy Schwartz, Vidur Joshi, Sameer Singh, Noah A. Smith:
Knowledge Enhanced Contextual Word Representations. CoRR abs/1909.04164 (2019) - 2018
- [c16]Roy Schwartz, Sam Thomson, Noah A. Smith:
Bridging CNNs, RNNs, and Weighted Finite-State Machines. ACL (1) 2018: 295-305 - [c15]Rowan Zellers, Yonatan Bisk, Roy Schwartz, Yejin Choi:
SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference. EMNLP 2018: 93-104 - [c14]Hao Peng, Roy Schwartz, Sam Thomson, Noah A. Smith:
Rational Recurrences. EMNLP 2018: 1203-1214 - [c13]Suchin Gururangan, Swabha Swayamdipta, Omer Levy, Roy Schwartz, Samuel R. Bowman, Noah A. Smith:
Annotation Artifacts in Natural Language Inference Data. NAACL-HLT (2) 2018: 107-112 - [c12]Dongyeop Kang, Waleed Ammar, Bhavana Dalvi, Madeleine van Zuylen, Sebastian Kohlmeier, Eduard H. Hovy, Roy Schwartz:
A Dataset of Peer Reviews (PeerRead): Collection, Insights and NLP Applications. NAACL-HLT 2018: 1647-1661 - [c11]Nelson F. Liu, Omer Levy, Roy Schwartz, Chenhao Tan, Noah A. Smith:
LSTMs Exploit Linguistic Attributes of Data. Rep4NLP@ACL 2018: 180-186 - [i8]Suchin Gururangan, Swabha Swayamdipta, Omer Levy, Roy Schwartz, Samuel R. Bowman, Noah A. Smith:
Annotation Artifacts in Natural Language Inference Data. CoRR abs/1803.02324 (2018) - [i7]Dongyeop Kang, Waleed Ammar, Bhavana Dalvi, Madeleine van Zuylen, Sebastian Kohlmeier, Eduard H. Hovy, Roy Schwartz:
A Dataset of Peer Reviews (PeerRead): Collection, Insights and NLP Applications. CoRR abs/1804.09635 (2018) - [i6]Roy Schwartz, Sam Thomson, Noah A. Smith:
SoPa: Bridging CNNs, RNNs, and Weighted Finite-State Machines. CoRR abs/1805.06061 (2018) - [i5]Nelson F. Liu, Omer Levy, Roy Schwartz, Chenhao Tan, Noah A. Smith:
LSTMs Exploit Linguistic Attributes of Data. CoRR abs/1805.11653 (2018) - [i4]Rowan Zellers, Yonatan Bisk, Roy Schwartz, Yejin Choi:
SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference. CoRR abs/1808.05326 (2018) - [i3]Hao Peng, Roy Schwartz, Sam Thomson, Noah A. Smith:
Rational Recurrences. CoRR abs/1808.09357 (2018) - 2017
- [c10]Roy Schwartz, Maarten Sap, Ioannis Konstas, Leila Zilles, Yejin Choi, Noah A. Smith:
The Effect of Different Writing Tasks on Linguistic Style: A Case Study of the ROC Story Cloze Task. CoNLL 2017: 15-25 - [c9]Ivan Vulic, Roy Schwartz, Ari Rappoport, Roi Reichart, Anna Korhonen:
Automatic Selection of Context Configurations for Improved Class-Specific Word Representations. CoNLL 2017: 112-122 - [c8]Roy Schwartz, Maarten Sap, Ioannis Konstas, Leila Zilles, Yejin Choi, Noah A. Smith:
Story Cloze Task: UW NLP System. LSDSem@EACL 2017: 52-55 - [i2]Roy Schwartz, Maarten Sap, Ioannis Konstas, Leila Zilles, Yejin Choi, Noah A. Smith:
The Effect of Different Writing Tasks on Linguistic Style: A Case Study of the ROC Story Cloze Task. CoRR abs/1702.01841 (2017) - 2016
- [c7]Roy Schwartz, Roi Reichart, Ari Rappoport:
Symmetric Patterns and Coordinations: Fast and Enhanced Representations of Verbs and Adjectives. HLT-NAACL 2016: 499-505 - [i1]Ivan Vulic, Roy Schwartz, Ari Rappoport, Roi Reichart, Anna Korhonen:
Automatic Selection of Context Configurations for Improved (and Fast) Class-Specific Word Representations. CoRR abs/1608.05528 (2016) - 2015
- [c6]Dana Rubinstein, Effi Levi, Roy Schwartz, Ari Rappoport:
How Well Do Distributional Models Capture Different Types of Semantic Knowledge? ACL (2) 2015: 726-730 - [c5]Roy Schwartz, Roi Reichart, Ari Rappoport:
Symmetric Pattern Based Word Embeddings for Improved Word Similarity Prediction. CoNLL 2015: 258-267 - 2014
- [c4]Roy Schwartz, Roi Reichart, Ari Rappoport:
Minimally Supervised Classification to Semantic Categories using Automatically Acquired Symmetric Patterns. COLING 2014: 1612-1623 - 2013
- [c3]Roy Schwartz, Oren Tsur, Ari Rappoport, Moshe Koppel:
Authorship Attribution of Micro-Messages. EMNLP 2013: 1880-1891 - 2012
- [c2]Roy Schwartz, Omri Abend, Ari Rappoport:
Learnability-Based Syntactic Annotation Design. COLING 2012: 2405-2422 - 2011
- [c1]Roy Schwartz, Omri Abend, Roi Reichart, Ari Rappoport:
Neutralizing Linguistically Problematic Annotations in Unsupervised Dependency Parsing Evaluation. ACL 2011: 663-672
Coauthor Index

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