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ORCIDEyal Shnarch
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2020 – today
- 2024
[c27]Shir Ashury-Tahan, Ariel Gera, Benjamin Sznajder, Leshem Choshen, Liat Ein-Dor, Eyal Shnarch:
Label-Efficient Model Selection for Text Generation. ACL (1) 2024: 8384-8402- [c26]Asaf Yehudai, Boaz Carmeli, Yosi Mass, Ofir Arviv, Nathaniel Mills, Eyal Shnarch, Leshem Choshen:
Achieving Human Parity in Content-Grounded Datasets Generation. ICLR 2024 - [c25]Yotam Perlitz, Elron Bandel, Ariel Gera, Ofir Arviv, Liat Ein-Dor, Eyal Shnarch, Noam Slonim, Michal Shmueli-Scheuer, Leshem Choshen:
Efficient Benchmarking (of Language Models). NAACL-HLT 2024: 2519-2536 - [i17]Asaf Yehudai, Boaz Carmeli, Yosi Mass, Ofir Arviv, Nathaniel Mills, Assaf Toledo, Eyal Shnarch, Leshem Choshen:
Genie: Achieving Human Parity in Content-Grounded Datasets Generation. CoRR abs/2401.14367 (2024) - [i16]Shir Ashury-Tahan, Benjamin Sznajder, Leshem Choshen, Liat Ein-Dor, Eyal Shnarch, Ariel Gera:
Label-Efficient Model Selection for Text Generation. CoRR abs/2402.07891 (2024) - [i15]Yotam Perlitz, Ariel Gera, Ofir Arviv, Asaf Yehudai, Elron Bandel, Eyal Shnarch, Michal Shmueli-Scheuer, Leshem Choshen:
Benchmark Agreement Testing Done Right: A Guide for LLM Benchmark Evaluation. CoRR abs/2407.13696 (2024) - 2023
- [c24]Ariel Gera, Roni Friedman, Ofir Arviv, Chulaka Gunasekara, Benjamin Sznajder, Noam Slonim, Eyal Shnarch:
The Benefits of Bad Advice: Autocontrastive Decoding across Model Layers. ACL (1) 2023: 10406-10420 - [i14]Ariel Gera, Roni Friedman, Ofir Arviv, Chulaka Gunasekara, Benjamin Sznajder, Noam Slonim, Eyal Shnarch:
The Benefits of Bad Advice: Autocontrastive Decoding across Model Layers. CoRR abs/2305.01628 (2023) - [i13]Yotam Perlitz, Elron Bandel, Ariel Gera, Ofir Arviv, Liat Ein-Dor, Eyal Shnarch, Noam Slonim, Michal Shmueli-Scheuer, Leshem Choshen:
Efficient Benchmarking (of Language Models). CoRR abs/2308.11696 (2023) - 2022
- [c23]Eyal Shnarch, Ariel Gera, Alon Halfon, Lena Dankin, Leshem Choshen, Ranit Aharonov, Noam Slonim:
Cluster & Tune: Boost Cold Start Performance in Text Classification. ACL (1) 2022: 7639-7653 - [c22]Eyal Shnarch, Alon Halfon, Ariel Gera, Marina Danilevsky, Yannis Katsis, Leshem Choshen, Martín Santillán Cooper, Dina Epelboim, Zheng Zhang, Dakuo Wang:
Label Sleuth: From Unlabeled Text to a Classifier in a Few Hours. EMNLP (Demos) 2022: 159-168 - [c21]Ariel Gera, Alon Halfon, Eyal Shnarch, Yotam Perlitz, Liat Ein-Dor, Noam Slonim:
Zero-Shot Text Classification with Self-Training. EMNLP 2022: 1107-1119 - [c20]Piyawat Lertvittayakumjorn, Leshem Choshen, Eyal Shnarch, Francesca Toni:
GrASP: A Library for Extracting and Exploring Human-Interpretable Textual Patterns. LREC 2022: 6093-6103 - [i12]Eyal Shnarch, Ariel Gera, Alon Halfon, Lena Dankin, Leshem Choshen, Ranit Aharonov, Noam Slonim:
Cluster & Tune: Boost Cold Start Performance in Text Classification. CoRR abs/2203.10581 (2022) - [i11]Benjamin Sznajder, Chulaka Gunasekara, Guy Lev, Sachin Joshi, Eyal Shnarch, Noam Slonim:
Heuristic-based Inter-training to Improve Few-shot Multi-perspective Dialog Summarization. CoRR abs/2203.15590 (2022) - [i10]Eyal Shnarch, Alon Halfon, Ariel Gera, Marina Danilevsky, Yannis Katsis, Leshem Choshen, Martín Santillán Cooper, Dina Epelboim, Zheng Zhang, Dakuo Wang, Lucy Yip, Liat Ein-Dor, Lena Dankin, Ilya Shnayderman, Ranit Aharonov, Yunyao Li, Naftali Liberman, Philip Levin Slesarev, Gwilym Newton, Shila Ofek-Koifman, Noam Slonim, Yoav Katz:
Label Sleuth: From Unlabeled Text to a Classifier in a Few Hours. CoRR abs/2208.01483 (2022) - [i9]Ariel Gera, Alon Halfon, Eyal Shnarch, Yotam Perlitz, Liat Ein-Dor, Noam Slonim:
Zero-Shot Text Classification with Self-Training. CoRR abs/2210.17541 (2022) - 2021
- [j1]Noam Slonim
, Yonatan Bilu, Carlos Alzate, Roy Bar-Haim, Ben Bogin, Francesca Bonin, Leshem Choshen, Edo Cohen-Karlik, Lena Dankin, Lilach Edelstein, Liat Ein-Dor, Roni Friedman-Melamed, Assaf Gavron, Ariel Gera, Martin Gleize, Shai Gretz, Dan Gutfreund, Alon Halfon, Daniel Hershcovich, Ron Hoory, Yufang Hou, Shay Hummel, Michal Jacovi, Charles Jochim, Yoav Kantor, Yoav Katz, David Konopnicki, Zvi Kons, Lili Kotlerman, Dalia Krieger, Dan Lahav, Tamar Lavee, Ran Levy, Naftali Liberman, Yosi Mass, Amir Menczel, Shachar Mirkin, Guy Moshkowich, Shila Ofek-Koifman, Matan Orbach, Ella Rabinovich, Ruty Rinott, Slava Shechtman, Dafna Sheinwald, Eyal Shnarch, Ilya Shnayderman, Aya Soffer, Artem Spector, Benjamin Sznajder, Assaf Toledo, Orith Toledo-Ronen, Elad Venezian, Ranit Aharonov:
An autonomous debating system. Nat. 591(7850): 379-384 (2021) - [i8]Piyawat Lertvittayakumjorn, Leshem Choshen, Eyal Shnarch, Francesca Toni:
GrASP: A Library for Extracting and Exploring Human-Interpretable Textual Patterns. CoRR abs/2104.03958 (2021) - 2020
- [c19]Liat Ein-Dor, Eyal Shnarch, Lena Dankin, Alon Halfon, Benjamin Sznajder, Ariel Gera, Carlos Alzate, Martin Gleize, Leshem Choshen, Yufang Hou, Yonatan Bilu, Ranit Aharonov, Noam Slonim:
Corpus Wide Argument Mining - A Working Solution. AAAI 2020: 7683-7691 - [c18]Eyal Shnarch, Leshem Choshen, Guy Moshkowich, Ranit Aharonov, Noam Slonim:
Unsupervised Expressive Rules Provide Explainability and Assist Human Experts Grasping New Domains. EMNLP (Findings) 2020: 2678-2697 - [c17]Liat Ein-Dor, Alon Halfon, Ariel Gera, Eyal Shnarch, Lena Dankin, Leshem Choshen, Marina Danilevsky, Ranit Aharonov, Yoav Katz, Noam Slonim:
Active Learning for BERT: An Empirical Study. EMNLP (1) 2020: 7949-7962 - [i7]Eyal Shnarch, Leshem Choshen, Guy Moshkowich, Noam Slonim, Ranit Aharonov:
Unsupervised Expressive Rules Provide Explainability and Assist Human Experts Grasping New Domains. CoRR abs/2010.09459 (2020)
2010 – 2019
- 2019
- [c16]Martin Gleize, Eyal Shnarch, Leshem Choshen, Lena Dankin, Guy Moshkowich, Ranit Aharonov, Noam Slonim:
Are You Convinced? Choosing the More Convincing Evidence with a Siamese Network. ACL (1) 2019: 967-976 - [i6]Martin Gleize, Eyal Shnarch, Leshem Choshen, Lena Dankin, Guy Moshkowich, Ranit Aharonov, Noam Slonim:
Are You Convinced? Choosing the More Convincing Evidence with a Siamese Network. CoRR abs/1907.08971 (2019) - [i5]Liat Ein-Dor, Eyal Shnarch, Lena Dankin, Alon Halfon, Benjamin Sznajder, Ariel Gera, Carlos Alzate, Martin Gleize, Leshem Choshen, Yufang Hou, Yonatan Bilu, Ranit Aharonov, Noam Slonim:
Corpus Wide Argument Mining - a Working Solution. CoRR abs/1911.10763 (2019) - 2018
- [c15]Eyal Shnarch, Carlos Alzate, Lena Dankin, Martin Gleize, Yufang Hou, Leshem Choshen, Ranit Aharonov, Noam Slonim:
Will it Blend? Blending Weak and Strong Labeled Data in a Neural Network for Argumentation Mining. ACL (2) 2018: 599-605 - [c14]Liat Ein-Dor, Alon Halfon, Yoav Kantor, Ran Levy, Yosi Mass, Ruty Rinott, Eyal Shnarch, Noam Slonim:
Semantic Relatedness of Wikipedia Concepts - Benchmark Data and a Working Solution. LREC 2018 - 2017
- [c13]Eyal Shnarch, Ran Levy, Vikas C. Raykar, Noam Slonim:
GRASP: Rich Patterns for Argumentation Mining. EMNLP 2017: 1345-1350 - 2013
- [c12]Eyal Shnarch, Erel Segal-haLevi, Jacob Goldberger, Ido Dagan:
PLIS: a Probabilistic Lexical Inference System. ACL (Conference System Demonstrations) 2013: 97-102 - 2012
- [c11]Eyal Shnarch, Ido Dagan, Jacob Goldberger:
A Probabilistic Lexical Model for Ranking Textual Inferences. *SEM@NAACL-HLT 2012: 237-245 - 2011
- [c10]Eyal Shnarch, Jacob Goldberger, Ido Dagan:
A Probabilistic Modeling Framework for Lexical Entailment. ACL (2) 2011: 558-563 - [c9]Eyal Shnarch, Jacob Goldberger, Ido Dagan:
Towards a Probabilistic Model for Lexical Entailment. TextInfer@EMNLP 2011: 10-19 - [i4]Asher Stern, Shachar Mirkin, Eyal Shnarch, Lili Kotlerman, Ido Dagan, Amnon Lotan, Jonathan Berant:
Knowledge and Tree-Edits in Learnable Entailment Proofs. TAC 2011 - 2010
- [c8]Shachar Mirkin, Jonathan Berant, Ido Dagan, Eyal Shnarch:
Recognising Entailment within Discourse. COLING 2010: 770-778 - [i3]Asher Stern, Eyal Shnarch, Shachar Mirkin, Lili Kotlerman, Naomi Zeichner, Ido Dagan, Amnon Lotan, Jonathan Berant:
Rule Chaining and Approximate Match in textual inference. TAC 2010
2000 – 2009
- 2009
- [c7]Eyal Shnarch, Libby Barak, Ido Dagan:
Extracting Lexical Reference Rules from Wikipedia. ACL/IJCNLP 2009: 450-458 - [c6]Shachar Mirkin, Ido Dagan, Eyal Shnarch:
Evaluating the Inferential Utility of Lexical-Semantic Resources. EACL 2009: 558-566 - [c5]Libby Barak, Ido Dagan, Eyal Shnarch:
Text Categorization from Category Name via Lexical Reference. HLT-NAACL (Short Papers) 2009: 33-36 - [i2]Shachar Mirkin, Roy Bar-Haim, Ido Dagan, Eyal Shnarch, Asher Stern, Idan Szpektor, Jonathan Berant:
Addressing Discourse and Document Structure in the RTE Search Task. TAC 2009 - 2008
- [c4]Ido Dagan, Roy Bar-Haim, Idan Szpektor, Iddo Greental, Eyal Shnarch:
Natural Language as the Basis for Meaning Representation and Inference. CICLing 2008: 151-170 - [i1]Roy Bar-Haim, Ido Dagan, Shachar Mirkin, Eyal Shnarch, Idan Szpektor, Jonathan Berant, Iddo Greental:
Efficient Semantic Deduction and Approximate Matching over Compact Parse Forests. TAC 2008 - 2007
- [c3]Roy Bar-Haim, Ido Dagan, Iddo Greental, Eyal Shnarch:
Semantic Inference at the Lexical-Syntactic Level. AAAI 2007: 871-876 - [c2]Idan Szpektor, Eyal Shnarch, Ido Dagan:
Instance-based Evaluation of Entailment Rule Acquisition. ACL 2007 - 2006
- [c1]Oren Glickman, Eyal Shnarch, Ido Dagan:
Lexical Reference: a Semantic Matching Subtask. EMNLP 2006: 172-179
Coauthor Index
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last updated on 2024-09-26 00:57 CEST by the dblp team
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