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Synthetic datasets have successfully been used to probe visual question-answering datasets for their reasoning abilities.
Quantifiers in natural languages: Some logical problems ii
Jaakko Hintikka. 1977 · 1977
Earlier work this paper cites.
Generalized quantifiers and natural language
Jon Barwise and Robin Cooper. 1981 · 1981
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
Model checking: Algorithmic verification and debugging
Edmund M. Clarke, E. Allen Emerson, and Joseph Sifakis. 2009 · 2009
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei. 2009 · 2009
Earlier work this paper cites.
Classical vs. modern squares of opposition, and beyond
Dag Westerståhl. 2012 · 2012
Earlier work this paper cites.
A multi-world approach to question answering about real-world scenes based on uncertain input
Mateusz Malinowski and Mario Fritz. 2014 · 2014
Earlier work this paper cites.
VQA: Visual Question Answering
Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C. Lawrence Zitnick, and Devi Parikh. 2015 · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2015 · 2015
Earlier work this paper cites.
Image retrieval using scene graphs
Justin Johnson, Ranjay Krishna, Michael Stark, Li-Jia Li, David Shamma, Michael Bernstein, and Li Fei-Fei. 2015 · 2015
Earlier work this paper cites.
Neural module networks
Jacob Andreas, Marcus Rohrbach, Trevor Darrell, and Dan Klein. 2016 · 2016
Earlier work this paper cites.
Hierarchical question-image co-attention for visual question answering
Jiasen Lu, Jianwei Yang, Dhruv Batra, and Devi Parikh. 2016 · 2016
Earlier work this paper cites.
Vqa: Visual question answering
Aishwarya Agrawal, Jiasen Lu, Stanislaw Antol, Margaret Mitchell, C. Lawrence Zitnick, Devi Parikh, and Dhruv Batra. 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.
A simple neural network module for relational reasoning
Adam Santoro, David Raposo, David G. T. Barrett, Mateusz Malinowski, Razvan Pascanu, Peter W. Battaglia, and Timothy P. Lillicrap. 2017 · 2017
Cited alongside, same era.
High-order attention models for visual question answering
Idan Schwartz, Alexander Schwing, and Tamir Hazan. 2017 · 2017
Cited alongside, same era.
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
Cited alongside, same era.
DROP: A reading comprehension benchmark requiring discrete reasoning over paragraphs
Dheeru Dua, Yizhong Wang, Pradeep Dasigi, Gabriel Stanovsky, Sameer Singh, and Matt Gardner. 2019 · 2019
Later among the works it cites.
Is the red square big? MALeViC: Modeling adjectives leveraging visual contexts
Sandro Pezzelle and Raquel Fernández. 2019 · 2019
Later among the works it cites.
Answer them all! toward universal visual question answering models
Robik Shrestha, Kushal Kafle, and Christopher Kanan. 2019 · 2019
Later among the works it cites.
Removing bias in multi-modal classifiers: Regularization by maximizing functional entropies
Itai Gat, Idan Schwartz, Alexander Schwing, and Tamir Hazan. 2020 · 2020
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TaxiNLI: Taking a ride up the NLU hill
Pratik Joshi, Somak Aditya, Aalok Sathe, and Monojit Choudhury. 2020 · 2020
Later among the works it cites.
Visual question answering: which investigated applications?
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Blender Online Community. 2018 · 2018
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Visual question answering : Datasets , methods , challenges and oppurtunities
Shayan Hassantabar. 2018 · 2018
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Compositional attention networks for machine reasoning
Drew A Hudson and Christopher D Manning. 2018 · 2018
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Bilinear Attention Networks
Jin-Hwa Kim, Jaehyun Jun, and Byoung-Tak Zhang. 2018 · 2018
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Learning conditioned graph structures for interpretable visual question answering
Will Norcliffe-Brown, Efstathios Vafeias, and Sarah Parisot. 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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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Silvio Barra, Carmen Bisogni, Maria De Marsico, and Stefano Ricciardi. 2021 · 2021
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Linguistic issues behind visual question answering
Raffaella Bernardi and Sandro Pezzelle. 2021 · 2021
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Part & whole extraction: Towards a deep understanding of quantitative facts for percentages in text
Lei Fang and Jian-Guang Lou. 2021 · 2021
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Visually grounded reasoning across languages and cultures
Fangyu Liu, Emanuele Bugliarello, Edoardo Maria Ponti, Siva Reddy, Nigel Collier, and Desmond Elliott. 2021 · 2021
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Probing cross-modal representations in multi-step relational reasoning
Iuliia Parfenova, Desmond Elliott, Raquel Fernández, and Sandro Pezzelle. 2021 · 2021
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CLEVR_HYP: A challenge dataset and baselines for visual question answering with hypothetical actions over images
Shailaja Keyur Sampat, Akshay Kumar, Yezhou Yang, and Chitta Baral. 2021 · 2021
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