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ORCIDRoy Schwartz 0001
Person information
- affiliation: Hebrew University of Jerusalem, Israel
Other persons with the same name
- Roy Schwartz
- Roy Schwartz 0002 — Technion, Haifa, Israel (and 2 more)
- Roy Schwartz 0004 — University College London, Institute of Health Informatics, UK (and 1 more)
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2020 – today
- 2024
[j4]Judit Ács
, Endre Hamerlik, Roy Schwartz, Noah A. Smith, András Kornai:
Morphosyntactic probing of multilingual BERT models. Nat. Lang. Eng. 30(4): 753-792 (2024)- [c45]Matanel Oren, Michael Hassid, Yarden Nir, Yossi Adi, Roy Schwartz:
Transformers are Multi-State RNNs. EMNLP 2024: 18724-18741 - [c44]Yuval Reif, Roy Schwartz:
Beyond Performance: Quantifying and Mitigating Label Bias in LLMs. NAACL-HLT 2024: 6784-6798 - [i52]Matanel Oren, Michael Hassid, Yossi Adi, Roy Schwartz:
Transformers are Multi-State RNNs. CoRR abs/2401.06104 (2024) - [i51]Michael Hassid, Tal Remez, Jonas Gehring, Roy Schwartz, Yossi Adi:
The Larger the Better? Improved LLM Code-Generation via Budget Reallocation. CoRR abs/2404.00725 (2024) - [i50]Yuval Reif, Roy Schwartz:
Beyond Performance: Quantifying and Mitigating Label Bias in LLMs. CoRR abs/2405.02743 (2024) - [i49]Jonathan Mamou, Oren Pereg, Daniel Korat, Moshe Berchansky, Nadav Timor, Moshe Wasserblat, Roy Schwartz:
Accelerating Speculative Decoding using Dynamic Speculation Length. CoRR abs/2405.04304 (2024) - [i48]Ilia Kuznetsov, Osama Mohammed Afzal, Koen Dercksen, Nils Dycke, Alexander Goldberg, Tom Hope, Dirk Hovy, Jonathan K. Kummerfeld, Anne Lauscher, Kevin Leyton-Brown, Sheng Lu, Mausam, Margot Mieskes, Aurélie Névéol, Danish Pruthi, Lizhen Qu, Roy Schwartz, Noah A. Smith, Thamar Solorio, Jingyan Wang, Xiaodan Zhu, Anna Rogers, Nihar B. Shah, Iryna Gurevych:
What Can Natural Language Processing Do for Peer Review? CoRR abs/2405.06563 (2024) - [i47]Amit Ben Artzy, Roy Schwartz:
Attend First, Consolidate Later: On the Importance of Attention in Different LLM Layers. CoRR abs/2409.03621 (2024) - [i46]Guy Kaplan, Matanel Oren, Yuval Reif, Roy Schwartz:
From Tokens to Words: On the Inner Lexicon of LLMs. CoRR abs/2410.05864 (2024) - 2023
- [j3]Marcos V. Treviso, Ji-Ung Lee, Tianchu Ji, Betty van Aken, Qingqing Cao, Manuel R. Ciosici, Michael Hassid, Kenneth Heafield, Sara Hooker, Colin Raffel, Pedro Henrique Martins, André F. T. Martins, Jessica Zosa Forde, Peter A. Milder, Edwin Simpson, Noam Slonim, Jesse Dodge, Emma Strubell, Niranjan Balasubramanian, Leon Derczynski, Iryna Gurevych, Roy Schwartz:
Efficient Methods for Natural Language Processing: A Survey. Trans. Assoc. Comput. Linguistics 11: 826-860 (2023) - [c43]Yonatan Bitton, Ron Yosef, Eliyahu Strugo, Dafna Shahaf, Roy Schwartz, Gabriel Stanovsky:
VASR: Visual Analogies of Situation Recognition. AAAI 2023: 241-249 - [c42]Aviad Sar-Shalom, Roy Schwartz:
Curating Datasets for Better Performance with Example Training Dynamics. ACL (Findings) 2023: 10597-10608 - [c41]Yuval Reif, Roy Schwartz:
Fighting Bias With Bias: Promoting Model Robustness by Amplifying Dataset Biases. ACL (Findings) 2023: 13169-13189 - [c40]Daniel Rotem, Michael Hassid, Jonathan Mamou, Roy Schwartz:
Finding the SWEET Spot: Analysis and Improvement of Adaptive Inference in Low Resource Settings. ACL (1) 2023: 14836-14851 - [c39]Nitzan Bitton Guetta, Yonatan Bitton, Jack Hessel, Ludwig Schmidt, Yuval Elovici, Gabriel Stanovsky, Roy Schwartz:
Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images. ICCV 2023: 2616-2627 - [c38]Michael Hassid, Tal Remez, Tu Anh Nguyen, Itai Gat, Alexis Conneau, Felix Kreuk, Jade Copet, Alexandre Défossez, Gabriel Synnaeve, Emmanuel Dupoux, Roy Schwartz, Yossi Adi:
Textually Pretrained Speech Language Models. NeurIPS 2023 - [i45]Nitzan Bitton Guetta, Yonatan Bitton, Jack Hessel, Ludwig Schmidt, Yuval Elovici, Gabriel Stanovsky, Roy Schwartz:
Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images. CoRR abs/2303.07274 (2023) - [i44]Michael Hassid, Tal Remez, Tu Anh Nguyen, Itai Gat, Alexis Conneau, Felix Kreuk, Jade Copet, Alexandre Défossez, Gabriel Synnaeve, Emmanuel Dupoux, Roy Schwartz, Yossi Adi:
Textually Pretrained Speech Language Models. CoRR abs/2305.13009 (2023) - [i43]Yuval Reif, Roy Schwartz:
Fighting Bias with Bias: Promoting Model Robustness by Amplifying Dataset Biases. CoRR abs/2305.18917 (2023) - [i42]Daniel Rotem, Michael Hassid, Jonathan Mamou, Roy Schwartz:
Finding the SWEET Spot: Analysis and Improvement of Adaptive Inference in Low Resource Settings. CoRR abs/2306.02307 (2023) - [i41]Judit Ács, Endre Hamerlik, Roy Schwartz, Noah A. Smith, András Kornai:
Morphosyntactic probing of multilingual BERT models. CoRR abs/2306.06205 (2023) - [i40]Ji-Ung Lee, Haritz Puerto, Betty van Aken, Yuki Arase, Jessica Zosa Forde, Leon Derczynski, Andreas Rücklé, Iryna Gurevych, Roy Schwartz, Emma Strubell, Jesse Dodge:
Surveying (Dis)Parities and Concerns of Compute Hungry NLP Research. CoRR abs/2306.16900 (2023) - [i39]Netta Madvil, Yonatan Bitton, Roy Schwartz:
Read, Look or Listen? What's Needed for Solving a Multimodal Dataset. CoRR abs/2307.04532 (2023) - 2022
- [c37]Inbal Magar, Roy Schwartz:
Data Contamination: From Memorization to Exploitation. ACL (2) 2022: 157-165 - [c36]Hao Peng, Jungo Kasai, Nikolaos Pappas, Dani Yogatama, Zhaofeng Wu, Lingpeng Kong, Roy Schwartz, Noah A. Smith:
ABC: Attention with Bounded-memory Control. ACL (1) 2022: 7469-7483 - [c35]Michael Hassid, Hao Peng, Daniel Rotem, Jungo Kasai, Ivan Montero, Noah A. Smith, Roy Schwartz:
How Much Does Attention Actually Attend? Questioning the Importance of Attention in Pretrained Transformers. EMNLP (Findings) 2022: 1403-1416 - [c34]Jesse Dodge, Taylor Prewitt, Remi Tachet des Combes, Erika Odmark, Roy Schwartz, Emma Strubell, Alexandra Sasha Luccioni, Noah A. Smith, Nicole DeCario, Will Buchanan:
Measuring the Carbon Intensity of AI in Cloud Instances. FAccT 2022: 1877-1894 - [c33]Roy Schwartz, Gabriel Stanovsky:
On the Limitations of Dataset Balancing: The Lost Battle Against Spurious Correlations. NAACL-HLT (Findings) 2022: 2182-2194 - [c32]Yonatan Bitton, Nitzan Bitton Guetta, Ron Yosef, Yuval Elovici, Mohit Bansal, Gabriel Stanovsky, Roy Schwartz:
WinoGAViL: Gamified Association Benchmark to Challenge Vision-and-Language Models. NeurIPS 2022 - [i38]Inbal Magar, Roy Schwartz:
Data Contamination: From Memorization to Exploitation. CoRR abs/2203.08242 (2022) - [i37]Jonathan Mamou, Oren Pereg, Moshe Wasserblat, Roy Schwartz:
TangoBERT: Reducing Inference Cost by using Cascaded Architecture. CoRR abs/2204.06271 (2022) - [i36]Roy Schwartz, Gabriel Stanovsky:
On the Limitations of Dataset Balancing: The Lost Battle Against Spurious Correlations. CoRR abs/2204.12708 (2022) - [i35]Jesse Dodge, Taylor Prewitt, Remi Tachet des Combes, Erika Odmark, Roy Schwartz, Emma Strubell, Alexandra Sasha Luccioni, Noah A. Smith, Nicole DeCario, Will Buchanan:
Measuring the Carbon Intensity of AI in Cloud Instances. CoRR abs/2206.05229 (2022) - [i34]Yarden Tal, Inbal Magar, Roy Schwartz:
Fewer Errors, but More Stereotypes? The Effect of Model Size on Gender Bias. CoRR abs/2206.09860 (2022) - [i33]Yonatan Bitton, Nitzan Bitton Guetta, Ron Yosef, Yuval Elovici, Mohit Bansal, Gabriel Stanovsky, Roy Schwartz:
WinoGAViL: Gamified Association Benchmark to Challenge Vision-and-Language Models. CoRR abs/2207.12576 (2022) - [i32]Marcos V. Treviso, Tianchu Ji, Ji-Ung Lee, Betty van Aken, Qingqing Cao, Manuel R. Ciosici, Michael Hassid, Kenneth Heafield, Sara Hooker, Pedro Henrique Martins, André F. T. Martins, Peter A. Milder, Colin Raffel, Edwin Simpson, Noam Slonim, Niranjan Balasubramanian, Leon Derczynski, Roy Schwartz:
Efficient Methods for Natural Language Processing: A Survey. CoRR abs/2209.00099 (2022) - [i31]Michael Hassid, Hao Peng, Daniel Rotem, Jungo Kasai, Ivan Montero, Noah A. Smith, Roy Schwartz:
How Much Does Attention Actually Attend? Questioning the Importance of Attention in Pretrained Transformers. CoRR abs/2211.03495 (2022) - [i30]Yonatan Bitton, Ron Yosef, Eli Strugo, Dafna Shahaf, Roy Schwartz, Gabriel Stanovsky:
VASR: Visual Analogies of Situation Recognition. CoRR abs/2212.04542 (2022) - [i29]Jesse Dodge, Iryna Gurevych, Roy Schwartz, Emma Strubell, Betty van Aken:
Efficient and Equitable Natural Language Processing in the Age of Deep Learning (Dagstuhl Seminar 22232). Dagstuhl Reports 12(6): 14-27 (2022) - 2021
- [j2]William Merrill, Yoav Goldberg, Roy Schwartz, Noah A. Smith:
Provable Limitations of Acquiring Meaning from Ungrounded Form: What Will Future Language Models Understand? Trans. Assoc. Comput. Linguistics 9: 1047-1060 (2021) - [c31]William Merrill, Vivek Ramanujan, Yoav Goldberg, Roy Schwartz, Noah A. Smith:
Effects of Parameter Norm Growth During Transformer Training: Inductive Bias from Gradient Descent. EMNLP (1) 2021: 1766-1781 - [c30]Yonatan Bitton, Michael Elhadad, Gabriel Stanovsky, Roy Schwartz:
Data Efficient Masked Language Modeling for Vision and Language. EMNLP (Findings) 2021: 3013-3028 - [c29]Jesse Dodge, Suchin Gururangan, Dallas Card, Roy Schwartz, Noah A. Smith:
Expected Validation Performance and Estimation of a Random Variable's Maximum. EMNLP (Findings) 2021: 4066-4073 - [c28]Hao Peng, Nikolaos Pappas, Dani Yogatama, Roy Schwartz, Noah A. Smith, Lingpeng Kong:
Random Feature Attention. ICLR 2021 - [c27]Yonatan Bitton, Gabriel Stanovsky, Roy Schwartz, Michael Elhadad:
Automatic Generation of Contrast Sets from Scene Graphs: Probing the Compositional Consistency of GQA. NAACL-HLT 2021: 94-105 - [c26]Tom Hope, Aida Amini, David Wadden, Madeleine van Zuylen, Sravanthi Parasa, Eric Horvitz, Daniel S. Weld, Roy Schwartz, Hannaneh Hajishirzi:
Extracting a Knowledge Base of Mechanisms from COVID-19 Papers. NAACL-HLT 2021: 4489-4503 - [i28]Hao Peng, Nikolaos Pappas, Dani Yogatama, Roy Schwartz, Noah A. Smith, Lingpeng Kong:
Random Feature Attention. CoRR abs/2103.02143 (2021) - [i27]Yonatan Bitton, Gabriel Stanovsky, Roy Schwartz, Michael Elhadad:
Automatic Generation of Contrast Sets from Scene Graphs: Probing the Compositional Consistency of GQA. CoRR abs/2103.09591 (2021) - [i26]William Merrill, Yoav Goldberg, Roy Schwartz, Noah A. Smith:
Provable Limitations of Acquiring Meaning from Ungrounded Form: What will Future Language Models Understand? CoRR abs/2104.10809 (2021) - [i25]William Merrill, Yoav Goldberg, Roy Schwartz, Noah A. Smith:
On the Power of Saturated Transformers: A View from Circuit Complexity. CoRR abs/2106.16213 (2021) - [i24]Yonatan Bitton, Gabriel Stanovsky, Michael Elhadad, Roy Schwartz:
Data Efficient Masked Language Modeling for Vision and Language. CoRR abs/2109.02040 (2021) - [i23]Jesse Dodge, Suchin Gururangan, Dallas Card, Roy Schwartz, Noah A. Smith:
Expected Validation Performance and Estimation of a Random Variable's Maximum. CoRR abs/2110.00613 (2021) - [i22]Hao Peng, Jungo Kasai, Nikolaos Pappas, Dani Yogatama, Zhaofeng Wu, Lingpeng Kong, Roy Schwartz, Noah A. Smith:
ABC: Attention with Bounded-memory Control. CoRR abs/2110.02488 (2021) - 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
- [b1]Roy Schwartz:
Pattern-Based methods for Improved Lexical Semantics and Word Embeddings (שער נוסף בעברית: : שיטות מבוססות תבניות לשיפור סמנטיקה לקסיקלית ושיכוני מילים.). Hebrew University of Jerusalem, Israel, 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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