Gabriel Stanovsky

According to our database, Gabriel Stanovsky authored at least 69 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

State of What Art? A Call for Multi-Prompt LLM Evaluation.

Moran Mizrahi, Guy Kaplan, Dan Malkin, Rotem Dror, Dafna Shahaf, Gabriel Stanovsky

Trans. Assoc. Comput. Linguistics, 2024

Looking Beyond The Top-1: Transformers Determine Top Tokens In Order.

Daria Lioubashevski, Tomer Schlank, Gabriel Stanovsky, Ariel Goldstein

CoRR, 2024

Surveying the Landscape of Image Captioning Evaluation: A Comprehensive Taxonomy and Novel Ensemble Method.

Uri Berger, Gabriel Stanovsky, Omri Abend, Lea Frermann

CoRR, 2024

SEAM: A Stochastic Benchmark for Multi-Document Tasks.

Gili Lior, Avi Caciularu, Arie Cattan, Shahar Levy, Ori Shapira, Gabriel Stanovsky

CoRR, 2024

In-Context Learning on a Budget: A Case Study in Named Entity Recognition.

Uri Berger, Tal Baumel, Gabriel Stanovsky

CoRR, 2024

A Nurse is Blue and Elephant is Rugby: Cross Domain Alignment in Large Language Models Reveal Human-like Patterns.

Asaf Yehudai, Taelin Karidi, Gabriel Stanovsky, Ariel Goldstein, Omri Abend

CoRR, 2024

Applying Intrinsic Debiasing on Downstream Tasks: Challenges and Considerations for Machine Translation.

Bar Iluz, Yanai Elazar, Asaf Yehudai, Gabriel Stanovsky

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Schema-Driven Information Extraction from Heterogeneous Tables.

Fan Bai, Junmo Kang, Gabriel Stanovsky, Dayne Freitag, Mark Dredze, Alan Ritter

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

K-QA: A Real-World Medical Q&A Benchmark.

Itay Manes, Naama Ronn, David Cohen, Ran Ilan Ber, Zehavi Horowitz-Kugler, Gabriel Stanovsky

Proceedings of the 23rd Workshop on Biomedical Natural Language Processing, 2024

Leveraging Collection-Wide Similarities for Unsupervised Document Structure Extraction.

Gili Lior, Yoav Goldberg, Gabriel Stanovsky

Proceedings of the Findings of the Association for Computational Linguistics, 2024

Do Zombies Understand? A Choose-Your-Own-Adventure Exploration of Machine Cognition.

Ariel Goldstein, Gabriel Stanovsky

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Instructed to Bias: Instruction-Tuned Language Models Exhibit Emergent Cognitive Bias.

Itay Itzhak, Gabriel Stanovsky, Nir Rosenfeld, Yonatan Belinkov

CoRR, 2023

Schema-Driven Information Extraction from Heterogeneous Tables.

Fan Bai, Junmo Kang, Gabriel Stanovsky, Dayne Freitag, Alan Ritter

CoRR, 2023

Exploring the Impact of Training Data Distribution and Subword Tokenization on Gender Bias in Machine Translation.

Bar Iluz, Tomasz Limisiewicz, Gabriel Stanovsky, David Marecek

Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, 2023

Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images.

Nitzan Bitton Guetta, Yonatan Bitton, Jack Hessel, Ludwig Schmidt, Yuval Elovici, Gabriel Stanovsky, Roy Schwartz

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

The Perfect Victim: Computational Analysis of Judicial Attitudes towards Victims of Sexual Violence.

Eliya Habba, Renana Keydar, Dan Bareket, Gabriel Stanovsky

Proceedings of the Nineteenth International Conference on Artificial Intelligence and Law, 2023

Evaluating and Improving the Coreference Capabilities of Machine Translation Models.

Asaf Yehudai, Arie Cattan, Omri Abend, Gabriel Stanovsky

Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023

A Large-Scale Multilingual Study of Visual Constraints on Linguistic Selection of Descriptions.

Uri Berger, Lea Frermann, Gabriel Stanovsky, Omri Abend

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2023, 2023

Comparing Humans and Models on a Similar Scale: Towards Cognitive Gender Bias Evaluation in Coreference Resolution.

Gili Lior, Gabriel Stanovsky

Proceedings of the 45th Annual Meeting of the Cognitive Science Society, 2023

Are Layout-Infused Language Models Robust to Layout Distribution Shifts? A Case Study with Scientific Documents.

Catherine Chen, Zejiang Shen, Dan Klein, Gabriel Stanovsky, Doug Downey, Kyle Lo

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

VASR: Visual Analogies of Situation Recognition.

Yonatan Bitton, Ron Yosef, Eliyahu Strugo, Dafna Shahaf, Roy Schwartz, Gabriel Stanovsky

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

You Can Have Your Data and Balance It Too: Towards Balanced and Efficient Multilingual Models.

Tomasz Limisiewicz, Dan Malkin, Gabriel Stanovsky

CoRR, 2022

Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022).

Guy Emerson, Natalie Schluter, Gabriel Stanovsky, Ritesh Kumar, Alexis Palmer, Nathan Schneider, Siddharth Singh, Shyam Ratan

Proceedings of the 16th International Workshop on Semantic Evaluation, SemEval@NAACL 2022, 2022

WinoGAViL: Gamified Association Benchmark to Challenge Vision-and-Language Models.

Yonatan Bitton, Nitzan Bitton Guetta, Ron Yosef, Yuval Elovici, Mohit Bansal, Gabriel Stanovsky, Roy Schwartz

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Balanced Data Approach for Evaluating Cross-Lingual Transfer: Mapping the Linguistic Blood Bank.

Dan Malkin, Tomasz Limisiewicz, Gabriel Stanovsky

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

A Computational Acquisition Model for Multimodal Word Categorization.

Uri Berger, Gabriel Stanovsky, Omri Abend, Lea Frermann

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

On the Limitations of Dataset Balancing: The Lost Battle Against Spurious Correlations.

Roy Schwartz, Gabriel Stanovsky

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

"Covid vaccine is against Covid but Oxford vaccine is made at Oxford!" Semantic Interpretation of Proper Noun Compounds.

Keshav Kolluru, Gabriel Stanovsky, Mausam

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

GENIE: Toward Reproducible and Standardized Human Evaluation for Text Generation.

Daniel Khashabi, Gabriel Stanovsky, Jonathan Bragg, Nicholas Lourie, Jungo Kasai, Yejin Choi, Noah A. Smith, Daniel S. Weld

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021

GENIE: A Leaderboard for Human-in-the-Loop Evaluation of Text Generation.

Daniel Khashabi, Gabriel Stanovsky, Jonathan Bragg, Nicholas Lourie, Jungo Kasai, Yejin Choi, Noah A. Smith, Daniel S. Weld

CoRR, 2021

Gender trends in computer science authorship.

Lucy Lu Wang, Gabriel Stanovsky, Luca Weihs, Oren Etzioni

Commun. ACM, 2021

Realistic Evaluation Principles for Cross-document Coreference Resolution.

Arie Cattan, Alon Eirew, Gabriel Stanovsky, Mandar Joshi, Ido Dagan

Proceedings of *SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics, 2021

Automatic Generation of Contrast Sets from Scene Graphs: Probing the Compositional Consistency of GQA.

Yonatan Bitton, Gabriel Stanovsky, Roy Schwartz, Michael Elhadad

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Collecting a Large-Scale Gender Bias Dataset for Coreference Resolution and Machine Translation.

Shahar Levy, Koren Lazar, Gabriel Stanovsky

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Filling the Gaps in Ancient Akkadian Texts: A Masked Language Modelling Approach.

Koren Lazar, Benny Saret, Asaf Yehudai, Wayne Horowitz, Nathan Wasserman, Gabriel Stanovsky

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Data Efficient Masked Language Modeling for Vision and Language.

Yonatan Bitton, Michael Elhadad, Gabriel Stanovsky, Roy Schwartz

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Process-Level Representation of Scientific Protocols with Interactive Annotation.

Ronen Tamari, Fan Bai, Alan Ritter, Gabriel Stanovsky

Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

Cross-document Coreference Resolution over Predicted Mentions.

Arie Cattan, Alon Eirew, Gabriel Stanovsky, Mandar Joshi, Ido Dagan

Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

Automated Extraction of Sentencing Decisions from Court Cases in the Hebrew Language.

Mohr Wenger, Tom Kalir, Noga Berger, Carmit Klar Chalamish, Renana Keydar, Gabriel Stanovsky

Proceedings of the Natural Legal Language Processing Workshop 2021, 2021

2020

Streamlining Cross-Document Coreference Resolution: Evaluation and Modeling.

Arie Cattan, Alon Eirew, Gabriel Stanovsky, Mandar Joshi, Ido Dagan

CoRR, 2020

Ecological Semantics: Programming Environments for Situated Language Understanding.

Ronen Tamari, Gabriel Stanovsky, Dafna Shahaf, Reut Tsarfaty

CoRR, 2020

Gender Coreference and Bias Evaluation at WMT 2020.

Tom Kocmi, Tomasz Limisiewicz, Gabriel Stanovsky

Proceedings of the Fifth Conference on Machine Translation, 2020

MOCHA: A Dataset for Training and Evaluating Generative Reading Comprehension Metrics.

Anthony Chen, Gabriel Stanovsky, Sameer Singh, Matt Gardner

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

The Right Tool for the Job: Matching Model and Instance Complexities.

Roy Schwartz, Gabriel Stanovsky, Swabha Swayamdipta, Jesse Dodge, Noah A. Smith

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Controlled Crowdsourcing for High-Quality QA-SRL Annotation.

Paul Roit, Ayal Klein, Daniela Stepanov, Jonathan Mamou, Julian Michael, Gabriel Stanovsky, Luke Zettlemoyer, Ido Dagan

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Active Learning for Coreference Resolution using Discrete Annotation.

Belinda Z. Li, Gabriel Stanovsky, Luke Zettlemoyer

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Crowdsourcing a High-Quality Gold Standard for QA-SRL.

Paul Roit, Ayal Klein, Daniela Stepanov, Jonathan Mamou, Julian Michael, Gabriel Stanovsky, Luke Zettlemoyer, Ido Dagan

CoRR, 2019

Yall should read this! Identifying Plurality in Second-Person Personal Pronouns in English Texts.

Gabriel Stanovsky, Ronen Tamari

CoRR, 2019

SemEval-2019 Task 10: Math Question Answering.

Mark Hopkins, Ronan Le Bras, Cristian Petrescu-Prahova, Gabriel Stanovsky, Hannaneh Hajishirzi, Rik Koncel-Kedziorski

Proceedings of the 13th International Workshop on Semantic Evaluation, 2019

DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs.

Dheeru Dua, Yizhong Wang, Pradeep Dasigi, Gabriel Stanovsky, Sameer Singh, Matt Gardner

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

On the Limits of Learning to Actively Learn Semantic Representations.

Omri Koshorek, Gabriel Stanovsky, Yichu Zhou, Vivek Srikumar, Jonathan Berant

Proceedings of the 23rd Conference on Computational Natural Language Learning, 2019

Y'all should read this! Identifying Plurality in Second-Person Personal Pronouns in English Texts.

Gabriel Stanovsky, Ronen Tamari

Proceedings of the 5th Workshop on Noisy User-generated Text, 2019

Evaluating Gender Bias in Machine Translation.

Gabriel Stanovsky, Noah A. Smith, Luke Zettlemoyer

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Evaluating Question Answering Evaluation.

Anthony Chen, Gabriel Stanovsky, Sameer Singh, Matt Gardner

Proceedings of the 2nd Workshop on Machine Reading for Question Answering, 2019

2018

Supervised Open Information Extraction.

Gabriel Stanovsky, Julian Michael, Luke Zettlemoyer, Ido Dagan

Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

Crowdsourcing Question-Answer Meaning Representations.

Julian Michael, Gabriel Stanovsky, Luheng He, Ido Dagan, Luke Zettlemoyer

Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

Spot the Odd Man Out: Exploring the Associative Power of Lexical Resources.

Gabriel Stanovsky, Mark Hopkins

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Semantics as a Foreign Language.

Gabriel Stanovsky, Ido Dagan

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

2017

Acquiring Predicate Paraphrases from News Tweets.

Vered Shwartz, Gabriel Stanovsky, Ido Dagan

Proceedings of the 6th Joint Conference on Lexical and Computational Semantics, 2017

A Consolidated Open Knowledge Representation for Multiple Texts.

Rachel Wities, Vered Shwartz, Gabriel Stanovsky, Meni Adler, Ori Shapira, Shyam Upadhyay, Dan Roth, Eugenio Martínez-Cámara, Iryna Gurevych, Ido Dagan

Proceedings of the 2nd Workshop on Linking Models of Lexical, 2017

Recognizing Mentions of Adverse Drug Reaction in Social Media Using Knowledge-Infused Recurrent Models.

Gabriel Stanovsky, Daniel Gruhl, Pablo N. Mendes

Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, 2017

Integrating Deep Linguistic Features in Factuality Prediction over Unified Datasets.

Gabriel Stanovsky, Judith Eckle-Kohler, Yevgeniy Puzikov, Ido Dagan, Iryna Gurevych

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

2016

Getting More Out Of Syntax with PropS.

Gabriel Stanovsky, Jessica Ficler, Ido Dagan, Yoav Goldberg

CoRR, 2016

Creating a Large Benchmark for Open Information Extraction.

Gabriel Stanovsky, Ido Dagan

Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016

Porting an Open Information Extraction System from English to German.

Tobias Falke, Gabriel Stanovsky, Iryna Gurevych, Ido Dagan

Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016

Modeling Extractive Sentence Intersection via Subtree Entailment.

Omer Levy, Ido Dagan, Gabriel Stanovsky, Judith Eckle-Kohler, Iryna Gurevych

Proceedings of the COLING 2016, 2016

Specifying and Annotating Reduced Argument Span Via QA-SRL.

Gabriel Stanovsky, Ido Dagan, Meni Adler

Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

Annotating and Predicting Non-Restrictive Noun Phrase Modifications.

Gabriel Stanovsky, Ido Dagan

Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

2015

Open IE as an Intermediate Structure for Semantic Tasks.

Gabriel Stanovsky, Ido Dagan, Mausam

Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, 2015