| 2026 | ACL | ScheMatiQ: From Research Question to Structured Data through Interactive Schema Discovery. | Shahar Levy, Eliya Habba, Reshef Mintz, Barak Raveh, Renana Keydar, Gabriel Stanovsky |
| 2026 | EACL | Leveraging Digitized Newspapers to Collect Summarization Data in Low-Resource Languages. | Noam Dahan, Omer Kidron, Gabriel Stanovsky |
| 2025 | ACL | DOVE: A Large-Scale Multi-Dimensional Predictions Dataset Towards Meaningful LLM Evaluation. | Eliya Habba, Ofir Arviv, Itay Itzhak, Yotam Perlitz, Elron Bandel, Leshem Choshen, Michal Shmueli-Scheuer, Gabriel Stanovsky |
| 2025 | ACL | Can LLMs Help Uncover Insights about LLMs? A Large-Scale, Evolving Literature Analysis of Frontier LLMs. | Jungsoo Park, Junmo Kang, Gabriel Stanovsky, Alan Ritter |
| 2025 | EMNLP | Time to Talk: LLM Agents for Asynchronous Group Communication in Mafia Games. | Niv Eckhaus, Uri Berger, Gabriel Stanovsky |
| 2025 | EMNLP | PromptSuite: A Task-Agnostic Framework for Multi-Prompt Generation. | Eliya Habba, Noam Dahan, Gili Lior, Gabriel Stanovsky |
| 2025 | EMNLP | More Documents, Same Length: Isolating the Challenge of Multiple Documents in RAG. | Shahar Levy, Nir Mazor, Lihi Shalmon, Michael Hassid, Gabriel Stanovsky |
| 2025 | EMNLP | ReliableEval: A Recipe for Stochastic LLM Evaluation via Method of Moments. | Gili Lior, Eliya Habba, Shahar Levy, Avi Caciularu, Gabriel Stanovsky |
| 2025 | EMNLP | Trust Me, I'm Wrong: LLMs Hallucinate with Certainty Despite Knowing the Answer. | Adi Simhi, Itay Itzhak, Fazl Barez, Gabriel Stanovsky, Yonatan Belinkov |
| 2025 | ICML | Looking Beyond the Top-1: Transformers Determine Top Tokens in Order. | Daria Lioubashevski, Tomer Schlank, Gabriel Stanovsky, Ariel Goldstein |
| 2025 | NAACL | The State and Fate of Summarization Datasets: A Survey. | Noam Dahan, Gabriel Stanovsky |
| 2024 | ACL | Do Zombies Understand? A Choose-Your-Own-Adventure Exploration of Machine Cognition. | Ariel Goldstein, Gabriel Stanovsky |
| 2024 | ACL | Leveraging Collection-Wide Similarities for Unsupervised Document Structure Extraction. | Gili Lior, Yoav Goldberg, Gabriel Stanovsky |
| 2024 | CogSci | 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 |
| 2024 | EMNLP | Schema-Driven Information Extraction from Heterogeneous Tables. | Fan Bai, Junmo Kang, Gabriel Stanovsky, Dayne Freitag, Mark Dredze, Alan Ritter |
| 2024 | EMNLP | Applying Intrinsic Debiasing on Downstream Tasks: Challenges and Considerations for Machine Translation. | Bar Iluz, Yanai Elazar, Asaf Yehudai, Gabriel Stanovsky |
| 2023 | AAAI | VASR: Visual Analogies of Situation Recognition. | Yonatan Bitton, Ron Yosef, Eliyahu Strugo, Dafna Shahaf, Roy Schwartz, Gabriel Stanovsky |
| 2023 | ACL | 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 |
| 2023 | CogSci | Comparing Humans and Models on a Similar Scale: Towards Cognitive Gender Bias Evaluation in Coreference Resolution. | Gili Lior, Gabriel Stanovsky |
| 2023 | EACL | A Large-Scale Multilingual Study of Visual Constraints on Linguistic Selection of Descriptions. | Uri Berger, Lea Frermann, Gabriel Stanovsky, Omri Abend |
| 2023 | EACL | Evaluating and Improving the Coreference Capabilities of Machine Translation Models. | Asaf Yehudai, Arie Cattan, Omri Abend, Gabriel Stanovsky |
| 2023 | ICAIL | The Perfect Victim: Computational Analysis of Judicial Attitudes towards Victims of Sexual Violence. | Eliya Habba, Renana Keydar, Dan Bareket, Gabriel Stanovsky |
| 2023 | ICCV | 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 |
| 2023 | IJCNLP | Exploring the Impact of Training Data Distribution and Subword Tokenization on Gender Bias in Machine Translation. | Bar Iluz, Tomasz Limisiewicz, Gabriel Stanovsky, David Marecek |
| 2022 | EMNLP | 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 |
| 2022 | EMNLP | "Covid vaccine is against Covid but Oxford vaccine is made at Oxford!" Semantic Interpretation of Proper Noun Compounds. | Keshav Kolluru, Gabriel Stanovsky, Mausam |
| 2022 | NAACL | On the Limitations of Dataset Balancing: The Lost Battle Against Spurious Correlations. | Roy Schwartz, Gabriel Stanovsky |
| 2022 | NAACL | A Computational Acquisition Model for Multimodal Word Categorization. | Uri Berger, Gabriel Stanovsky, Omri Abend, Lea Frermann |
| 2022 | NAACL | A Balanced Data Approach for Evaluating Cross-Lingual Transfer: Mapping the Linguistic Blood Bank. | Dan Malkin, Tomasz Limisiewicz, Gabriel Stanovsky |
| 2021 | ACL | Cross-document Coreference Resolution over Predicted Mentions. | Arie Cattan, Alon Eirew, Gabriel Stanovsky, Mandar Joshi, Ido Dagan |
| 2021 | EACL | Process-Level Representation of Scientific Protocols with Interactive Annotation. | Ronen Tamari, Fan Bai, Alan Ritter, Gabriel Stanovsky |
| 2021 | EMNLP | Data Efficient Masked Language Modeling for Vision and Language. | Yonatan Bitton, Michael Elhadad, Gabriel Stanovsky, Roy Schwartz |
| 2021 | EMNLP | Filling the Gaps in Ancient Akkadian Texts: A Masked Language Modelling Approach. | Koren Lazar, Benny Saret, Asaf Yehudai, Wayne Horowitz, Nathan Wasserman, Gabriel Stanovsky |
| 2021 | EMNLP | Collecting a Large-Scale Gender Bias Dataset for Coreference Resolution and Machine Translation. | Shahar Levy, Koren Lazar, Gabriel Stanovsky |
| 2021 | NAACL | Automatic Generation of Contrast Sets from Scene Graphs: Probing the Compositional Consistency of GQA. | Yonatan Bitton, Gabriel Stanovsky, Roy Schwartz, Michael Elhadad |
| 2020 | ACL | Active Learning for Coreference Resolution using Discrete Annotation. | Belinda Z. Li, Gabriel Stanovsky, Luke Zettlemoyer |
| 2020 | ACL | Controlled Crowdsourcing for High-Quality QA-SRL Annotation. | Paul Roit, Ayal Klein, Daniela Stepanov, Jonathan Mamou, Julian Michael, Gabriel Stanovsky, Luke Zettlemoyer, Ido Dagan |
| 2020 | ACL | The Right Tool for the Job: Matching Model and Instance Complexities. | Roy Schwartz, Gabriel Stanovsky, Swabha Swayamdipta, Jesse Dodge, Noah A. Smith |
| 2020 | EMNLP | MOCHA: A Dataset for Training and Evaluating Generative Reading Comprehension Metrics. | Anthony Chen, Gabriel Stanovsky, Sameer Singh, Matt Gardner |
| 2019 | ACL | Evaluating Gender Bias in Machine Translation. | Gabriel Stanovsky, Noah A. Smith, Luke Zettlemoyer |
| 2019 | CoNLL | On the Limits of Learning to Actively Learn Semantic Representations. | Omri Koshorek, Gabriel Stanovsky, Yichu Zhou, Vivek Srikumar, Jonathan Berant |
| 2019 | NAACL | DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs. | Dheeru Dua, Yizhong Wang, Pradeep Dasigi, Gabriel Stanovsky, Sameer Singh, Matt Gardner |
| 2018 | EMNLP | Semantics as a Foreign Language. | Gabriel Stanovsky, Ido Dagan |
| 2018 | EMNLP | Spot the Odd Man Out: Exploring the Associative Power of Lexical Resources. | Gabriel Stanovsky, Mark Hopkins |
| 2018 | NAACL | Crowdsourcing Question-Answer Meaning Representations. | Julian Michael, Gabriel Stanovsky, Luheng He, Ido Dagan, Luke Zettlemoyer |
| 2018 | NAACL | Supervised Open Information Extraction. | Gabriel Stanovsky, Julian Michael, Luke Zettlemoyer, Ido Dagan |
| 2017 | ACL | Integrating Deep Linguistic Features in Factuality Prediction over Unified Datasets. | Gabriel Stanovsky, Judith Eckle-Kohler, Yevgeniy Puzikov, Ido Dagan, Iryna Gurevych |
| 2017 | EACL | Recognizing Mentions of Adverse Drug Reaction in Social Media Using Knowledge-Infused Recurrent Models. | Gabriel Stanovsky, Daniel Gruhl, Pablo N. Mendes |
| 2017 | EACL | A Consolidated Open Knowledge Representation for Multiple Texts. | Rachel Wities, Vered Shwartz, Gabriel Stanovsky, Meni Adler, Ori Shapira, Shyam Upadhyay, Dan Roth, Eugenio Martnez-Cmara, Iryna Gurevych, Ido Dagan |
| 2016 | ACL | Annotating and Predicting Non-Restrictive Noun Phrase Modifications. | Gabriel Stanovsky, Ido Dagan |
| 2016 | ACL | Specifying and Annotating Reduced Argument Span Via QA-SRL. | Gabriel Stanovsky, Ido Dagan, Meni Adler |
| 2016 | COLING | Modeling Extractive Sentence Intersection via Subtree Entailment. | Omer Levy, Ido Dagan, Gabriel Stanovsky, Judith Eckle-Kohler, Iryna Gurevych |
| 2016 | EMNLP | Porting an Open Information Extraction System from English to German. | Tobias Falke, Gabriel Stanovsky, Iryna Gurevych, Ido Dagan |
| 2016 | EMNLP | Creating a Large Benchmark for Open Information Extraction. | Gabriel Stanovsky, Ido Dagan |
| 2015 | ACL | Open IE as an Intermediate Structure for Semantic Tasks. | Gabriel Stanovsky, Ido Dagan, Mausam |