Language Generation with Recurrent Generative Adversarial Networks without Pre-training. - Ofir Press; Amir Bar; Ben Bogin; Jonathan Berant; Lior Wolf (CoRR, 2017)

Towards an argumentative content search engine using weak supervision. - Ran Levy 001; Ben Bogin; Shai Gretz; Ranit Aharonov; Noam Slonim (COLING, 2018)

Emergence of Communication in an Interactive World with Consistent Speakers. - Ben Bogin; Mor Geva; Jonathan Berant (CoRR, 2018)

Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing. - Ben Bogin; Jonathan Berant; Matt Gardner 001 (ACL (1), 2019)

Global Reasoning over Database Structures for Text-to-SQL Parsing. - Ben Bogin; Matt Gardner 001; Jonathan Berant (EMNLP/IJCNLP (1), 2019)

Grammar-based Neural Text-to-SQL Generation. - Kevin Lin; Ben Bogin; Mark Neumann; Jonathan Berant; Matt Gardner 001 (CoRR, 2019)

Obtaining Faithful Interpretations from Compositional Neural Networks. - Sanjay Subramanian; Ben Bogin; Nitish Gupta; Tomer Wolfson; Sameer Singh 001; Jonathan Berant; Matt Gardner 001 (ACL, 2020)

Evaluating Models' Local Decision Boundaries via Contrast Sets. - Matt Gardner 001; Yoav Artzi; Victoria Basmova; Jonathan Berant; Ben Bogin; Sihao Chen; Pradeep Dasigi; Dheeru Dua; Yanai Elazar; Ananth Gottumukkala; Nitish Gupta; Hannaneh Hajishirzi; et al. (EMNLP (Findings), 2020)

MedICaT: A Dataset of Medical Images, Captions, and Textual References. - Sanjay Subramanian; Lucy Lu Wang; Ben Bogin; Sachin Mehta; Madeleine van Zuylen; Sravanthi Parasa; Sameer Singh 001; Matt Gardner 001; Hannaneh Hajishirzi (EMNLP (Findings), 2020)

Evaluating NLP Models via Contrast Sets. - Matt Gardner 001; Yoav Artzi; Victoria Basmova; Jonathan Berant; Ben Bogin; Sihao Chen; Pradeep Dasigi; Dheeru Dua; Yanai Elazar; Ananth Gottumukkala; Nitish Gupta; Hanna Hajishirzi; et al. (CoRR, 2020)

COVR: A Test-Bed for Visually Grounded Compositional Generalization with Real Images. - Ben Bogin; Shivanshu Gupta; Matt Gardner 001; Jonathan Berant (EMNLP (1), 2021)

Text-to-SQL in the Wild: A Naturally-Occurring Dataset Based on Stack Exchange Data. - Moshe Hazoom; Vibhor Malik; Ben Bogin (CoRR, 2021)

An autonomous debating system. - 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; et al. (Nat., 2021)

Latent Compositional Representations Improve Systematic Generalization in Grounded Question Answering. - Ben Bogin; Sanjay Subramanian; Matt Gardner 001; Jonathan Berant (Trans. Assoc. Comput. Linguistics, 2021)

Training Vision-Language Models with Less Bimodal Supervision. - Elad Segal; Ben Bogin; Jonathan Berant (AKBC, 2022)

Unobserved Local Structures Make Compositional Generalization Hard. - Ben Bogin; Shivanshu Gupta; Jonathan Berant (EMNLP, 2022)

Diverse Demonstrations Improve In-context Compositional Generalization. - Itay Levy; Ben Bogin; Jonathan Berant (ACL (1), 2023)

Answering Questions by Meta-Reasoning over Multiple Chains of Thought. - Ori Yoran; Tomer Wolfson; Ben Bogin; Uri Katz; Daniel Deutch; Jonathan Berant (EMNLP, 2023)

Latent Trees for Compositional Generalization. - Jonathan Herzig; Jonathan Berant; Ben Bogin (Compendium of Neurosymbolic Artificial Intelligence, 2023)

Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research. - Luca Soldaini; Rodney Kinney; Akshita Bhagia; Dustin Schwenk; David Atkinson; Russell Authur; Ben Bogin; Khyathi Raghavi Chandu; Jennifer Dumas; Yanai Elazar; Valentin Hofmann; Ananya Harsh Jha; et al. (ACL (1), 2024)

SUPER: Evaluating Agents on Setting Up and Executing Tasks from Research Repositories. - Ben Bogin; Kejuan Yang; Shashank Gupta; Kyle Richardson 001; Erin Bransom; Peter Clark; Ashish Sabharwal; Tushar Khot (EMNLP, 2024)

AssistantBench: Can Web Agents Solve Realistic and Time-Consuming Tasks? - Ori Yoran; Samuel Joseph Amouyal; Chaitanya Malaviya; Ben Bogin; Ofir Press; Jonathan Berant (EMNLP, 2024)

Leveraging Code to Improve In-Context Learning for Semantic Parsing. - Ben Bogin; Shivanshu Gupta; Peter Clark; Ashish Sabharwal (NAACL-HLT, 2024)

Aurora-M: The First Open Source Multilingual Language Model Red-teamed according to the U.S. Executive Order. - Taishi Nakamura; Mayank Mishra; Simone Tedeschi; Yekun Chai; Jason T. Stillerman; Felix Friedrich; Prateek Yadav; Tanmay Laud; Minh Chien Vu; Terry Yue Zhuo; Diganta Misra; Ben Bogin; et al. (CoRR, 2024)

Aurora-M: Open Source Continual Pre-training for Multilingual Language and Code. - Taishi Nakamura; Mayank Mishra; Simone Tedeschi; Yekun Chai; Jason T. Stillerman; Felix Friedrich; Prateek Yadav; Tanmay Laud; Minh Chien Vu; Terry Yue Zhuo; Diganta Misra; Ben Bogin; et al. (COLING (Industry), 2025)

DataDecide: How to Predict Best Pretraining Data with Small Experiments. - Ian Magnusson; Nguyen Tai; Ben Bogin; David Heineman; Jena D. Hwang; Luca Soldaini; Akshita Bhagia; Jiacheng Liu 010; Dirk Groeneveld; Oyvind Tafjord; Noah A. Smith; Pang Wei Koh; et al. (CoRR, 2025)

Leveraging In-Context Learning for Language Model Agents. - Shivanshu Gupta; Sameer Singh 001; Ashish Sabharwal; Tushar Khot; Ben Bogin (CoRR, 2025)