Short Bio

I am a Computer Science PhD student in the Natural Language Processing lab at Bar-Ilan University, under the supervision of Prof. Ido Dagan.

My research focuses on recognizing lexical semantic relations between words and phrases. I work on ontological relationships e.g., cat is a type of animal, tail is a part of cat; interpreting noun-compounds, e.g. olive oil is oil made of olives while baby oil is oil for babies; and identifying predicate paraphrases, e.g. that X die at Y may have the same meaning as X live until Y in certain contexts.

I completed my B.Sc. (2013) and M.Sc. (2015) in Computer Science in Bar-Ilan University.
My complete CV can be found here.


Publications

Conference Papers

Paraphrase to Explicate: Revealing Implicit Noun-Compound Relations
Vered Shwartz and Ido Dagan. ACL 2018.
bib long

Breaking NLI Systems with Sentences that Require Simple Lexical Inferences
Max Glockner, Vered Shwartz, and Yoav Goldberg. ACL 2018.
bib short

Olive Oil Is Made of Olives, Baby Oil Is Made for Babies: Interpreting Noun Compounds Using Paraphrases in a Neural Model
Vered Shwartz and Chris Waterson. NAACL 2018.
paper bib code dataset short

Integrating Multiplicative Features into Supervised Distributional Methods for Lexical Entailment
Tu Vu and Vered Shwartz. *SEM 2018.
paper bib short

Neural Disambiguation of Causal Lexical Markers Based on Context
Eugenio Martinez Camara, Vered Shwartz, Iryna Gurevych, and Ido Dagan. IWCS 2017.
paper bib code long

Acquiring Predicate Paraphrases from News Tweets
Vered Shwartz, Gabriel Stanovsky and Ido Dagan. *SEM 2017.
paper bib code poster short

Learning Antonyms with Paraphrases and a Morphology-aware Neural Network
Sneha Rajana, Chris Callison-Burch, Marianna Apidianaki and Vered Shwartz. *SEM 2017.
paper bib code long

Hypernyms under Siege: Linguistically-motivated Artillery for Hypernymy Detection
Vered Shwartz, Enrico Santus, and Dominik Schlechtweg. EACL 2017.
paper bib code slides long

Improving Hypernymy Detection with an Integrated Path-based and Distributional Method
Vered Shwartz, Yoav Goldberg and Ido Dagan. ACL 2016.
paper bib code dataset slides video long outstanding paper

Adding Context to Semantic Data-Driven Paraphrasing
Vered Shwartz and Ido Dagan. *SEM 2016.
paper bib dataset AMT templates & guidelines poster short best paper

Learning to Exploit Structured Resources for Lexical Inference
Vered Shwartz, Omer Levy, Ido Dagan and Jacob Goldberger. CoNLL 2015.
paper bib code supplementary material dataset video poster long

Multi-Level Alignments As An Extensible Representation Basis for Textual Entailment Algorithms
Tae-Gil Noh, Sebastian Padó, Vered Shwartz, Ido Dagan, Vivi Nastase,
Kathrin Eichler, Lili Kotlerman and Meni Adler. *SEM 2015.
paper bib poster short



Workshop Papers

SemEval-2018 Task 9: Hypernym Discovery
Jose Camacho-Collados, Claudio Delli Bovi, Luis Espinosa-Anke, Sergio Oramas, Tommaso Pasini, Enrico Santus,
Vered Shwartz, Roberto Navigli, and Horacio Saggion.
Proceedings of the 12th International Workshop on Semantic Evaluation (SemEval) @ NAACL 2018.
bib long

A Consolidated Open Knowledge Representation for Multiple Texts
Rachel Wities, Vered Shwartz, Gabriel Stanovsky, Meni Adler, Ori Shapira, Shyam Upadhyay,
Dan Roth, Eugenio Martinez Camara, Iryna Gurevych and Ido Dagan.
Proceedings of the 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-level Semantics (LSDSem) @ EACL 2017.
paper bib code long

Path-based vs. Distributional Information in Recognizing Lexical Semantic Relations
Vered Shwartz and Ido Dagan.
Proceedings of the 5th Workshop on Cognitive Aspects of the Lexicon (CogALex-V) @ COLING 2016.
paper bib code slides long

CogALex-V Shared Task: LexNET - Integrated Path-based and Distributional Method for the Identification of Semantic Relations
Vered Shwartz and Ido Dagan.
Proceedings of the 5th Workshop on Cognitive Aspects of the Lexicon (CogALex-V) @ COLING 2016.
paper bib code slides long


Invited Talks

How are you two related? Corpus-based Learning of Lexical Semantic Relations
January 2018, Workshop on Wordnets and Word Embeddings, 9th Global Wordnet Conference, Singapore
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Acquiring Lexical Semantic Knowledge
January 2018, Computer Science Department Seminar, NUS School of Computing, Singapore
slides

Acquiring Lexical Semantic Knowledge
December 2017, Advanced Topics NLP Seminar, Tel-Aviv University, Israel
slides

Acquiring Lexical Semantic Knowledge
November 2017, Google Research, Israel
slides

Recognizing Lexical Inference
August 2016, UKP lab, Darmstadt University, Germany
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Recognizing Lexical Inference
April 2016, ProbModels Reading Group, EdinburghNLP, University of Edinburgh, Scotland
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Recognizing Lexical Inference
April 2016, Thomson Reuters, Israel
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Recognizing Lexical Inference
February 2016, Intel, Israel

Learning To Exploit Structured Resources for Lexical Inference
April 2015, IBM Research, Israel