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2020 – today
- 2023
[i58]Armen Aghajanyan, Lili Yu, Alexis Conneau, Wei-Ning Hsu, Karen Hambardzumyan, Susan Zhang, Stephen Roller, Naman Goyal, Omer Levy, Luke Zettlemoyer:
Scaling Laws for Generative Mixed-Modal Language Models. CoRR abs/2301.03728 (2023)- [i57]Yuval Kirstain, Omer Levy, Adam Polyak:
X&Fuse: Fusing Visual Information in Text-to-Image Generation. CoRR abs/2303.01000 (2023) - 2022
- [c55]Uri Shaham, Omer Levy:
What Do You Get When You Cross Beam Search with Nucleus Sampling? Insights@ACL 2022: 38-45 - [c54]Yuval Kirstain, Patrick S. H. Lewis, Sebastian Riedel, Omer Levy:
A Few More Examples May Be Worth Billions of Parameters. EMNLP (Findings) 2022: 1017-1029 - [c53]Adi Haviv, Ori Ram, Ofir Press, Peter Izsak, Omer Levy:
Transformer Language Models without Positional Encodings Still Learn Positional Information. EMNLP (Findings) 2022: 1382-1390 - [c52]Uri Shaham, Elad Segal, Maor Ivgi, Avia Efrat, Ori Yoran, Adi Haviv, Ankit Gupta, Wenhan Xiong, Mor Geva, Jonathan Berant, Omer Levy:
SCROLLS: Standardized CompaRison Over Long Language Sequences. EMNLP 2022: 12007-12021 - [c51]Wenhan Xiong, Barlas Oguz, Anchit Gupta, Xilun Chen, Diana Liskovich, Omer Levy, Scott Yih, Yashar Mehdad:
Simple Local Attentions Remain Competitive for Long-Context Tasks. NAACL-HLT 2022: 1975-1986 - [c50]Ori Ram, Gal Shachaf, Omer Levy, Jonathan Berant, Amir Globerson:
Learning to Retrieve Passages without Supervision. NAACL-HLT 2022: 2687-2700 - [c49]Itay Itzhak, Omer Levy:
Models In a Spelling Bee: Language Models Implicitly Learn the Character Composition of Tokens. NAACL-HLT 2022: 5061-5068 - [i56]Uri Shaham, Elad Segal, Maor Ivgi, Avia Efrat, Ori Yoran, Adi Haviv, Ankit Gupta, Wenhan Xiong, Mor Geva, Jonathan Berant, Omer Levy:
SCROLLS: Standardized CompaRison Over Long Language Sequences. CoRR abs/2201.03533 (2022) - [i55]Avital Friedland, Jonathan Zeltser, Omer Levy:
Are Mutually Intelligible Languages Easier to Translate? CoRR abs/2201.13072 (2022) - [i54]Adi Haviv, Ori Ram, Ofir Press, Peter Izsak, Omer Levy:
Transformer Language Models without Positional Encodings Still Learn Positional Information. CoRR abs/2203.16634 (2022) - [i53]Omri Keren, Tal Avinari, Reut Tsarfaty, Omer Levy:
Breaking Character: Are Subwords Good Enough for MRLs After All? CoRR abs/2204.04748 (2022) - [i52]Or Honovich, Uri Shaham, Samuel R. Bowman, Omer Levy:
Instruction Induction: From Few Examples to Natural Language Task Descriptions. CoRR abs/2205.10782 (2022) - [i51]Avia Efrat, Or Honovich, Omer Levy:
LMentry: A Language Model Benchmark of Elementary Language Tasks. CoRR abs/2211.02069 (2022) - [i50]Uri Shaham, Maha Elbayad, Vedanuj Goswami, Omer Levy, Shruti Bhosale:
Causes and Cures for Interference in Multilingual Translation. CoRR abs/2212.07530 (2022) - [i49]Lior Vassertail, Omer Levy:
A Simple Baseline for Beam Search Reranking. CoRR abs/2212.08926 (2022) - [i48]Or Honovich, Thomas Scialom, Omer Levy, Timo Schick:
Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor. CoRR abs/2212.09689 (2022) - 2021
- [j5]Omer Levy, Dror G. Feitelson
:
Understanding large-scale software systems - structure and flows. Empir. Softw. Eng. 26(3): 48 (2021) - [c48]Yuval Kirstain, Ori Ram, Omer Levy:
Coreference Resolution without Span Representations. ACL/IJCNLP (2) 2021: 14-19 - [c47]Ori Ram, Yuval Kirstain, Jonathan Berant, Amir Globerson, Omer Levy:
Few-Shot Question Answering by Pretraining Span Selection. ACL/IJCNLP (1) 2021: 3066-3079 - [c46]Avia Efrat, Uri Shaham, Dan Kilman, Omer Levy:
Cryptonite: A Cryptic Crossword Benchmark for Extreme Ambiguity in Language. EMNLP (1) 2021: 4186-4192 - [c45]Mor Geva, Roei Schuster, Jonathan Berant, Omer Levy:
Transformer Feed-Forward Layers Are Key-Value Memories. EMNLP (1) 2021: 5484-5495 - [c44]Peter Izsak, Moshe Berchansky, Omer Levy:
How to Train BERT with an Academic Budget. EMNLP (1) 2021: 10644-10652 - [c43]Uri Shaham, Omer Levy:
Neural Machine Translation without Embeddings. NAACL-HLT 2021: 181-186 - [c42]Adi Haviv, Lior Vassertail, Omer Levy:
Can Latent Alignments Improve Autoregressive Machine Translation? NAACL-HLT 2021: 2637-2641 - [i47]Yuval Kirstain, Ori Ram, Omer Levy:
Coreference Resolution without Span Representations. CoRR abs/2101.00434 (2021) - [i46]Ori Ram, Yuval Kirstain, Jonathan Berant, Amir Globerson, Omer Levy:
Few-Shot Question Answering by Pretraining Span Selection. CoRR abs/2101.00438 (2021) - [i45]Avia Efrat, Uri Shaham, Dan Kilman, Omer Levy:
Cryptonite: A Cryptic Crossword Benchmark for Extreme Ambiguity in Language. CoRR abs/2103.01242 (2021) - [i44]Peter Izsak, Moshe Berchansky, Omer Levy:
How to Train BERT with an Academic Budget. CoRR abs/2104.07705 (2021) - [i43]Adi Haviv, Lior Vassertail, Omer Levy:
Can Latent Alignments Improve Autoregressive Machine Translation? CoRR abs/2104.09554 (2021) - [i42]Uri Shaham, Omer Levy:
What Do You Get When You Cross Beam Search with Nucleus Sampling? CoRR abs/2107.09729 (2021) - [i41]Or Castel, Ori Ram, Avia Efrat, Omer Levy:
How Optimal is Greedy Decoding for Extractive Question Answering? CoRR abs/2108.05857 (2021) - [i40]Itay Itzhak, Omer Levy:
Models In a Spelling Bee: Language Models Implicitly Learn the Character Composition of Tokens. CoRR abs/2108.11193 (2021) - [i39]Omri Keren, Omer Levy:
ParaShoot: A Hebrew Question Answering Dataset. CoRR abs/2109.11314 (2021) - [i38]Yuval Kirstain, Patrick S. H. Lewis, Sebastian Riedel, Omer Levy:
A Few More Examples May Be Worth Billions of Parameters. CoRR abs/2110.04374 (2021) - [i37]Wenhan Xiong, Barlas Oguz, Anchit Gupta, Xilun Chen, Diana Liskovich, Omer Levy, Wen-tau Yih, Yashar Mehdad:
Simple Local Attentions Remain Competitive for Long-Context Tasks. CoRR abs/2112.07210 (2021) - [i36]Ori Ram, Gal Shachaf, Omer Levy, Jonathan Berant, Amir Globerson:
Learning to Retrieve Passages without Supervision. CoRR abs/2112.07708 (2021) - 2020
- [j4]Christopher D. Manning, Kevin Clark, John Hewitt, Urvashi Khandelwal, Omer Levy:
Emergent linguistic structure in artificial neural networks trained by self-supervision. Proc. Natl. Acad. Sci. USA 117(48): 30046-30054 (2020) - [j3]Mandar Joshi, Danqi Chen, Yinhan Liu, Daniel S. Weld, Luke Zettlemoyer, Omer Levy:
SpanBERT: Improving Pre-training by Representing and Predicting Spans. Trans. Assoc. Comput. Linguistics 8: 64-77 (2020) - [c41]Ofir Press, Noah A. Smith, Omer Levy:
Improving Transformer Models by Reordering their Sublayers. ACL 2020: 2996-3005 - [c40]Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, Luke Zettlemoyer:
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension. ACL 2020: 7871-7880 - [c39]Jiezhong Qiu, Hao Ma, Omer Levy, Wen-tau Yih, Sinong Wang, Jie Tang:
Blockwise Self-Attention for Long Document Understanding. EMNLP (Findings) 2020: 2555-2565 - [c38]Urvashi Khandelwal, Omer Levy, Dan Jurafsky, Luke Zettlemoyer, Mike Lewis:
Generalization through Memorization: Nearest Neighbor Language Models. ICLR 2020 - [c37]Uri Alon, Roy Sadaka, Omer Levy, Eran Yahav:
Structural Language Models of Code. ICML 2020: 245-256 - [c36]Marjan Ghazvininejad, Vladimir Karpukhin, Luke Zettlemoyer, Omer Levy:
Aligned Cross Entropy for Non-Autoregressive Machine Translation. ICML 2020: 3515-3523 - [i35]Marjan Ghazvininejad, Omer Levy, Luke Zettlemoyer:
Semi-Autoregressive Training Improves Mask-Predict Decoding. CoRR abs/2001.08785 (2020) - [i34]Marjan Ghazvininejad, Vladimir Karpukhin, Luke Zettlemoyer, Omer Levy:
Aligned Cross Entropy for Non-Autoregressive Machine Translation. CoRR abs/2004.01655 (2020) - [i33]Uri Shaham, Omer Levy:
Neural Machine Translation without Embeddings. CoRR abs/2008.09396 (2020) - [i32]Avia Efrat, Omer Levy:
The Turking Test: Can Language Models Understand Instructions? CoRR abs/2010.11982 (2020) - [i31]Mor Geva, Roei Schuster, Jonathan Berant, Omer Levy:
Transformer Feed-Forward Layers Are Key-Value Memories. CoRR abs/2012.14913 (2020)
2010 – 2019
- 2019
- [j2]Uri Alon, Meital Zilberstein, Omer Levy, Eran Yahav:
code2vec: learning distributed representations of code. Proc. ACM Program. Lang. 3(POPL): 40:1-40:29 (2019) - [c35]Vladimir Karpukhin, Omer Levy, Jacob Eisenstein, Marjan Ghazvininejad:
Training on Synthetic Noise Improves Robustness to Natural Noise in Machine Translation. W-NUT@EMNLP 2019: 42-47 - [c34]Kevin Clark, Urvashi Khandelwal, Omer Levy, Christopher D. Manning:
What Does BERT Look at? An Analysis of BERT's Attention. BlackboxNLP@ACL 2019: 276-286 - [c33]Mandar Joshi, Omer Levy, Luke Zettlemoyer, Daniel S. Weld:
BERT for Coreference Resolution: Baselines and Analysis. EMNLP/IJCNLP (1) 2019: 5802-5807 - [c32]Marjan Ghazvininejad, Omer Levy, Yinhan Liu, Luke Zettlemoyer:
Mask-Predict: Parallel Decoding of Conditional Masked Language Models. EMNLP/IJCNLP (1) 2019: 6111-6120 - [c31]Uri Alon, Shaked Brody, Omer Levy, Eran Yahav:
code2seq: Generating Sequences from Structured Representations of Code. ICLR (Poster) 2019 - [c30]Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, Samuel R. Bowman:
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding. ICLR (Poster) 2019 - [c29]Omer Levy, Dror G. Feitelson:
Understanding large-scale software: a hierarchical view. ICPC 2019: 283-293 - [c28]Mandar Joshi, Eunsol Choi, Omer Levy, Daniel S. Weld, Luke Zettlemoyer:
pair2vec: Compositional Word-Pair Embeddings for Cross-Sentence Inference. NAACL-HLT (1) 2019: 3597-3608 - [c27]Alex Wang, Yada Pruksachatkun, Nikita Nangia, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, Samuel R. Bowman:
SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems. NeurIPS 2019: 3261-3275 - [c26]Paul Michel, Omer Levy, Graham Neubig:
Are Sixteen Heads Really Better than One? NeurIPS 2019: 14014-14024 - [i30]Vladimir Karpukhin, Omer Levy, Jacob Eisenstein, Marjan Ghazvininejad:
Training on Synthetic Noise Improves Robustness to Natural Noise in Machine Translation. CoRR abs/1902.01509 (2019) - [i29]Marjan Ghazvininejad, Omer Levy, Yinhan Liu, Luke Zettlemoyer:
Constant-Time Machine Translation with Conditional Masked Language Models. CoRR abs/1904.09324 (2019) - [i28]Alex Wang, Yada Pruksachatkun, Nikita Nangia, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, Samuel R. Bowman:
SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems. CoRR abs/1905.00537 (2019) - [i27]Paul Michel, Omer Levy, Graham Neubig:
Are Sixteen Heads Really Better than One? CoRR abs/1905.10650 (2019) - [i26]Kevin Clark, Urvashi Khandelwal, Omer Levy, Christopher D. Manning:
What Does BERT Look At? An Analysis of BERT's Attention. CoRR abs/1906.04341 (2019) - [i25]Mandar Joshi, Danqi Chen, Yinhan Liu, Daniel S. Weld, Luke Zettlemoyer, Omer Levy:
SpanBERT: Improving Pre-training by Representing and Predicting Spans. CoRR abs/1907.10529 (2019) - [i24]Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, Veselin Stoyanov:
RoBERTa: A Robustly Optimized BERT Pretraining Approach. CoRR abs/1907.11692 (2019) - [i23]Mandar Joshi, Omer Levy, Daniel S. Weld, Luke Zettlemoyer:
BERT for Coreference Resolution: Baselines and Analysis. CoRR abs/1908.09091 (2019) - [i22]Uri Alon, Roy Sadaka, Omer Levy, Eran Yahav:
Structural Language Models for Any-Code Generation. CoRR abs/1910.00577 (2019) - [i21]Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, Luke Zettlemoyer:
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension. CoRR abs/1910.13461 (2019) - [i20]Urvashi Khandelwal, Omer Levy, Dan Jurafsky, Luke Zettlemoyer, Mike Lewis:
Generalization through Memorization: Nearest Neighbor Language Models. CoRR abs/1911.00172 (2019) - [i19]Jiezhong Qiu, Hao Ma, Omer Levy, Scott Wen-tau Yih, Sinong Wang, Jie Tang:
Blockwise Self-Attention for Long Document Understanding. CoRR abs/1911.02972 (2019) - [i18]Ofir Press, Noah A. Smith, Omer Levy:
Improving Transformer Models by Reordering their Sublayers. CoRR abs/1911.03864 (2019) - 2018
- [c25]Terra Blevins, Omer Levy, Luke Zettlemoyer:
Deep RNNs Encode Soft Hierarchical Syntax. ACL (2) 2018: 14-19 - [c24]Eunsol Choi, Omer Levy, Yejin Choi, Luke Zettlemoyer:
Ultra-Fine Entity Typing. ACL (1) 2018: 87-96 - [c23]Luheng He, Kenton Lee, Omer Levy, Luke Zettlemoyer:
Jointly Predicting Predicates and Arguments in Neural Semantic Role Labeling. ACL (2) 2018: 364-369 - [c22]Omer Levy, Kenton Lee, Nicholas FitzGerald, Luke Zettlemoyer:
Long Short-Term Memory as a Dynamically Computed Element-wise Weighted Sum. ACL (2) 2018: 732-739 - [c21]Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, Samuel R. Bowman:
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding. BlackboxNLP@EMNLP 2018: 353-355 - [c20]Antoine Bosselut, Omer Levy, Ari Holtzman, Corin Ennis, Dieter Fox, Yejin Choi:
Simulating Action Dynamics with Neural Process Networks. ICLR (Poster) 2018 - [c19]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 - [c18]Uri Alon, Meital Zilberstein, Omer Levy, Eran Yahav:
A general path-based representation for predicting program properties. PLDI 2018: 404-419 - [c17]Nelson F. Liu, Omer Levy, Roy Schwartz, Chenhao Tan, Noah A. Smith:
LSTMs Exploit Linguistic Attributes of Data. Rep4NLP@ACL 2018: 180-186 - [i17]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) - [i16]Uri Alon, Meital Zilberstein, Omer Levy, Eran Yahav:
code2vec: Learning Distributed Representations of Code. CoRR abs/1803.09473 (2018) - [i15]Uri Alon, Meital Zilberstein, Omer Levy, Eran Yahav:
A General Path-Based Representation for Predicting Program Properties. CoRR abs/1803.09544 (2018) - [i14]Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, Samuel R. Bowman:
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding. CoRR abs/1804.07461 (2018) - [i13]Omer Levy, Kenton Lee, Nicholas FitzGerald, Luke Zettlemoyer:
Long Short-Term Memory as a Dynamically Computed Element-wise Weighted Sum. CoRR abs/1805.03716 (2018) - [i12]Terra Blevins, Omer Levy, Luke Zettlemoyer:
Deep RNNs Encode Soft Hierarchical Syntax. CoRR abs/1805.04218 (2018) - [i11]Luheng He, Kenton Lee, Omer Levy, Luke Zettlemoyer:
Jointly Predicting Predicates and Arguments in Neural Semantic Role Labeling. CoRR abs/1805.04787 (2018) - [i10]Nelson F. Liu, Omer Levy, Roy Schwartz, Chenhao Tan, Noah A. Smith:
LSTMs Exploit Linguistic Attributes of Data. CoRR abs/1805.11653 (2018) - [i9]Eunsol Choi, Omer Levy, Yejin Choi, Luke Zettlemoyer:
Ultra-Fine Entity Typing. CoRR abs/1807.04905 (2018) - [i8]Uri Alon, Omer Levy, Eran Yahav:
code2seq: Generating Sequences from Structured Representations of Code. CoRR abs/1808.01400 (2018) - [i7]Mandar Joshi, Eunsol Choi, Omer Levy, Daniel S. Weld, Luke Zettlemoyer:
pair2vec: Compositional Word-Pair Embeddings for Cross-Sentence Inference. CoRR abs/1810.08854 (2018) - 2017
- [c16]Yotam Eshel, Noam Cohen, Kira Radinsky, Shaul Markovitch, Ikuya Yamada, Omer Levy:
Named Entity Disambiguation for Noisy Text. CoNLL 2017: 58-68 - [c15]Omer Levy, Minjoon Seo, Eunsol Choi, Luke Zettlemoyer:
Zero-Shot Relation Extraction via Reading Comprehension. CoNLL 2017: 333-342 - [c14]Omer Levy, Anders Søgaard, Yoav Goldberg:
A Strong Baseline for Learning Cross-Lingual Word Embeddings from Sentence Alignments. EACL (1) 2017: 765-774 - [e1]Samuel R. Bowman, Yoav Goldberg, Felix Hill, Angeliki Lazaridou, Omer Levy, Roi Reichart, Anders Søgaard:
Proceedings of the 2nd Workshop on Evaluating Vector Space Representations for NLP, RepEval@EMNLP 2017, Copenhagen, Denmark, September 8, 2017. Association for Computational Linguistics 2017, ISBN 978-1-945626-90-6 [contents] - [i6]Kenton Lee, Omer Levy, Luke Zettlemoyer:
Recurrent Additive Networks. CoRR abs/1705.07393 (2017) - [i5]Omer Levy, Minjoon Seo, Eunsol Choi, Luke Zettlemoyer:
Zero-Shot Relation Extraction via Reading Comprehension. CoRR abs/1706.04115 (2017) - [i4]Yotam Eshel, Noam Cohen, Kira Radinsky, Shaul Markovitch, Ikuya Yamada, Omer Levy:
Named Entity Disambiguation for Noisy Text. CoRR abs/1706.09147 (2017) - [i3]Antoine Bosselut, Omer Levy, Ari Holtzman, Corin Ennis, Dieter Fox, Yejin Choi:
Simulating Action Dynamics with Neural Process Networks. CoRR abs/1711.05313 (2017) - 2016
- [c13]Omer Levy, Ido Dagan:
Annotating Relation Inference in Context via Question Answering. ACL (2) 2016 - [c12]Omer Levy, Ido Dagan, Gabriel Stanovsky, Judith Eckle-Kohler, Iryna Gurevych:
Modeling Extractive Sentence Intersection via Subtree Entailment. COLING 2016: 2891-2901 - [i2]Omer Levy, Anders Søgaard, Yoav Goldberg:
Reconsidering Cross-lingual Word Embeddings. CoRR abs/1608.05426 (2016) - 2015
- [j1]Omer Levy, Yoav Goldberg, Ido Dagan:
Improving Distributional Similarity with Lessons Learned from Word Embeddings. Trans. Assoc. Comput. Linguistics 3: 211-225 (2015) - [c11]Vered Shwartz, Omer Levy, Ido Dagan, Jacob Goldberger:
Learning to Exploit Structured Resources for Lexical Inference. CoNLL 2015: 175-184 - [c10]Oren Melamud, Omer Levy, Ido Dagan:
A Simple Word Embedding Model for Lexical Substitution. VS@HLT-NAACL 2015: 1-7 - [c9]Omer Levy, Steffen Remus, Chris Biemann, Ido Dagan:
Do Supervised Distributional Methods Really Learn Lexical Inference Relations? HLT-NAACL 2015: 970-976 - 2014
- [c8]Bernardo Magnini, Roberto Zanoli, Ido Dagan, Kathrin Eichler, Guenter Neumann, Tae-Gil Noh, Sebastian Padó, Asher Stern, Omer Levy:
The Excitement Open Platform for Textual Inferences. ACL (System Demonstrations) 2014: 43-48 - [c7]Omer Levy, Yoav Goldberg:
Dependency-Based Word Embeddings. ACL (2) 2014: 302-308 - [c6]Omer Levy, Ido Dagan, Jacob Goldberger:
Focused Entailment Graphs for Open IE Propositions. CoNLL 2014: 87-97 - [c5]Omer Levy, Yoav Goldberg:
Linguistic Regularities in Sparse and Explicit Word Representations. CoNLL 2014: 171-180 - [c4]Omer Levy, Yoav Goldberg:
Neural Word Embedding as Implicit Matrix Factorization. NIPS 2014: 2177-2185 - [i1]Yoav Goldberg, Omer Levy:
word2vec Explained: deriving Mikolov et al.'s negative-sampling word-embedding method. CoRR abs/1402.3722 (2014) - 2013
- [c3]Omer Levy, Torsten Zesch, Ido Dagan, Iryna Gurevych:
Recognizing Partial Textual Entailment. ACL (2) 2013: 451-455 - [c2]Omer Levy, Torsten Zesch, Ido Dagan, Iryna Gurevych:
UKP-BIU: Similarity and Entailment Metrics for Student Response Analysis. SemEval@NAACL-HLT 2013: 285-289 - 2012
- [c1]Omer Levy, Shaul Markovitch:
Teaching Machines to Learn by Metaphors. AAAI 2012