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While models for Visual Question Answering (VQA) have steadily improved over the years, interacting with one quickly reveals that these models lack consistency.
Gqa: a new dataset for compositional question answering over real-world images
Drew A Hudson and Christopher D Manning. 2019 · 1902
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Cycle-consistency for robust visual question answering
Meet Shah, Xinlei Chen, Marcus Rohrbach, and Devi Parikh. 2019 · 1902
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The search for robustness in natural language understanding
Manfred Stede. 1992 · 1992
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Introduction to Logic and to the Methodology of the Deductive Sciences
Alfred Tarski and Jan Tarski. 1994 · 1994
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George A Miller. 1995 · 1995
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
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The unabridged journals of Sylvia Plath
Sylvia Plath. 2007 · 2007
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013 · 2013
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Vqa: Visual question answering
Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C Lawrence Zitnick, and Devi Parikh. 2015 · 2015
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
Cited alongside, same era.
Generating natural questions about an image
Nasrin Mostafazadeh, Ishan Misra, Jacob Devlin, Margaret Mitchell, Xiaodong He, and Lucy Vanderwende. 2016 · 2016
Cited alongside, same era.
Question relevance in vqa: identifying non-visual and false-premise questions
Arijit Ray, Gordon Christie, Mohit Bansal, Dhruv Batra, and Devi Parikh. 2016 · 2016
Cited alongside, same era.
Automatic generation of grounded visual questions
Shijie Zhang, Lizhen Qu, Shaodi You, Zhenglu Yang, and Jiawan Zhang. 2016 · 2016
Visual genome: Connecting language and vision using crowdsourced dense image annotations
Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidis, Li-Jia Li, David A Shamma, et al. 2017 · 2017
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Robust training under linguistic adversity
Yitong Li, Trevor Cohn, and Timothy Baldwin. 2017 · 2017
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The promise of premise: Harnessing question premises in visual question answering
Aroma Mahendru, Viraj Prabhu, Akrit Mohapatra, Dhruv Batra, and Stefan Lee. 2017 · 2017
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Ishan Misra, Ross Girshick, Rob Fergus, Martial Hebert, Abhinav Gupta, and Laurens van der Maaten. 2017 · 2017
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Evaluating quality of chatbots and intelligent conversational agents
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Cited alongside, same era.
C-vqa: A compositional split of the visual question answering (vqa) v1. 0 dataset
Aishwarya Agrawal, Aniruddha Kembhavi, Dhruv Batra, and Devi Parikh. 2017 · 2017
Cited alongside, same era.
Making the v in vqa matter: Elevating the role of image understanding in visual question answering
Yash Goyal, Tejas Khot, Douglas Summers-Stay, Dhruv Batra, and Devi Parikh. 2017 · 2017
Cited alongside, same era.
Clevr: A diagnostic dataset for compositional language and elementary visual reasoning
Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Li Fei-Fei, C Lawrence Zitnick, and Ross Girshick. 2017 · 2017
Cited alongside, same era.
Nicole M Radziwill and Morgan C Benton. 2017 · 2017
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Bottom-up and top-down attention for image captioning and visual question answering
Peter Anderson, Xiaodong He, Chris Buehler, Damien Teney, Mark Johnson, Stephen Gould, and Lei Zhang. 2018 · 2018
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Overcoming language priors in visual question answering with adversarial regularization
Sainandan Ramakrishnan, Aishwarya Agrawal, and Stefan Lee. 2018 · 2018
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Fooling vision and language models despite localization and attention mechanism
Xiaojun Xu, Xinyun Chen, Chang Liu, Anna Rohrbach, Trevor Darrell, and Dawn Song. 2018 · 2018
Later among the works it cites.