Ben Bogin

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Tel Aviv University

MedICaT: A Dataset of Medical Images, Captions, and Textual References

Understanding the relationship between figures and text is key to scient...
10/12/2020 ∙ by Sanjay Subramanian, et al. ∙ 18 ∙ share

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Latent Compositional Representations Improve Systematic Generalization in Grounded Question Answering

Answering questions that involve multi-step reasoning requires decomposi...
07/01/2020 ∙ by Ben Bogin, et al. ∙ 7 ∙ share

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Obtaining Faithful Interpretations from Compositional Neural Networks

Neural module networks (NMNs) are a popular approach for modeling compos...
05/02/2020 ∙ by Sanjay Subramanian, et al. ∙ 22 ∙ share

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Evaluating NLP Models via Contrast Sets

Standard test sets for supervised learning evaluate in-distribution gene...
04/06/2020 ∙ by Matt Gardner, et al. ∙ 0 ∙ share

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Global Reasoning over Database Structures for Text-to-SQL Parsing

State-of-the-art semantic parsers rely on auto-regressive decoding, emit...
08/29/2019 ∙ by Ben Bogin, et al. ∙ 0 ∙ share

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Grammar-based Neural Text-to-SQL Generation

The sequence-to-sequence paradigm employed by neural text-to-SQL models ...
05/30/2019 ∙ by Kevin Lin, et al. ∙ 0 ∙ share

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Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing

Research on parsing language to SQL has largely ignored the structure of...
05/15/2019 ∙ by Ben Bogin, et al. ∙ 0 ∙ share

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Emergence of Communication in an Interactive World with Consistent Speakers

Training agents to communicate with one another given task-based supervi...
09/03/2018 ∙ by Ben Bogin, et al. ∙ 0 ∙ share

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Language Generation with Recurrent Generative Adversarial Networks without Pre-training

Generative Adversarial Networks (GANs) have shown great promise recently...
06/05/2017 ∙ by Ofir Press, et al. ∙ 0 ∙ share

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Ben Bogin

Featured Co-authors

Lior Wolf

Noah A. Smith

Hannaneh Hajishirzi

Jonathan Berant

Sameer Singh

Matt Gardner

Daniel Khashabi

Yoav Artzi

Kevin Lin

Eric Wallace

Qiang Ning

MedICaT: A Dataset of Medical Images, Captions, and Textual References

Latent Compositional Representations Improve Systematic Generalization in Grounded Question Answering

Obtaining Faithful Interpretations from Compositional Neural Networks

Evaluating NLP Models via Contrast Sets

Global Reasoning over Database Structures for Text-to-SQL Parsing

Grammar-based Neural Text-to-SQL Generation

Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing

Emergence of Communication in an Interactive World with Consistent Speakers

Language Generation with Recurrent Generative Adversarial Networks without Pre-training