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For vision-and-language reasoning tasks, both fully connectionist, end-to-end methods and hybrid, neuro-symbolic methods have achieved high in-distribution performance.
VQA: Visual Question Answering
Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C. Lawrence Zitnick, and Devi Parikh. 2015 · 2015
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Faster R-CNN: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun. 2015 · 2015
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Situation recognition: Visual semantic role labeling for image understanding
Mark Yatskar, Luke Zettlemoyer, and Ali Farhadi. 2016 · 2016
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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 B. Girshick. 2017 · 2017
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A corpus of natural language for visual reasoning
Alane Suhr, Mike Lewis, James Yeh, and Yoav Artzi. 2017 · 2017
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Neural scene de-rendering
Jiajun Wu, Joshua B Tenenbaum, and Pushmeet Kohli. 2017 · 2017
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Compositional attention networks for machine reasoning
Drew A. Hudson and Christopher D. Manning. 2018 · 2018
Earlier work this paper cites.
Neural-Symbolic VQA: Disentangling reasoning from vision and language understanding
Kexin Yi, Jiajun Wu, Chuang Gan, Antonio Torralba, Pushmeet Kohli, and Joshua B. Tenenbaum. 2018 · 2018
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VisualBERT: A simple and performant baseline for vision and language
Liunian Harold Li, Mark Yatskar, Da Yin, Cho-Jui Hsieh, and Kai-Wei Chang. 2019 · 2019
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ViLBERT: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks
Jiasen Lu, Dhruv Batra, Devi Parikh, and Stefan Lee. 2019 · 2019
Earlier work this paper cites.
The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision
Jiayuan Mao, Chuang Gan, Pushmeet Kohli, Joshua B. Tenenbaum, and Jiajun Wu. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Cited alongside, same era.
Are red roses red? evaluating consistency of question-answering models
Marco Tulio Ribeiro, Carlos Guestrin, and Sameer Singh. 2019 · 2019
Cited alongside, same era.
A corpus for reasoning about natural language grounded in photographs
Alane Suhr, Stephanie Zhou, Ally Zhang, Iris Zhang, Huajun Bai, and Yoav Artzi. 2019 · 2019
Cited alongside, same era.
LXMERT: Learning cross-modality encoder representations from transformers
Hao Tan and Mohit Bansal. 2019 · 2019
Cited alongside, same era.
UNITER: Universal image-text representation learning
Yen-Chun Chen, Linjie Li, Licheng Yu, Ahmed El Kholy, Faisal Ahmed, Zhe Gan, Yu Cheng, and Jingjing Liu. 2020 · 2020
Cited alongside, same era.
Utility is in the eye of the user: A critique of NLP leaderboards
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
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Unbiased scene graph generation from biased training
Kaihua Tang, Yulei Niu, Jianqiang Huang, Jiaxin Shi, and Hanwang Zhang. 2020 · 2020
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Automatic generation of contrast sets from scene graphs: Probing the compositional consistency of GQA
Yonatan Bitton, Gabriel Stanovsky, Roy Schwartz, and Michael Elhadad. 2021 · 2021
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COVR: A test-bed for visually grounded compositional generalization with real images
Ben Bogin, Shivanshu Gupta, Matt Gardner, and Jonathan Berant. 2021 · 2021
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Unlocking compositional generalization in pre-trained models using intermediate representations
Jonathan Herzig, Peter Shaw, Ming-Wei Chang, Kelvin Guu, Panupong Pasupat, and Yuan Zhang. 2021 · 2021
Later among the works it cites.
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Kawin Ethayarajh and Dan Jurafsky. 2020 · 2020
Cited alongside, same era.
Evaluating models’ local decision boundaries via contrast sets
Matt Gardner, Yoav Artzi, Victoria Basmov, Jonathan Berant, Ben Bogin, Sihao Chen, Pradeep Dasigi, Dheeru Dua, Yanai Elazar, Ananth Gottumukkala, Nitish Gupta, Hannaneh Hajishirzi, Gabriel Ilharco, Daniel Khashabi, Kevin Lin, Jiangming Liu, Nelson F. Liu, Phoebe Mulcaire, Qiang Ning, Sameer Singh, Noah A. Smith, Sanjay Subramanian, Reut Tsarfaty, Eric Wallace, Ally Zhang, and Ben Zhou. 2020 · 2020
Cited alongside, same era.
BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
Cited alongside, same era.
A closer look at the robustness of vision-and-language pre-trained models
Linjie Li, Zhe Gan, and Jingjing Liu. 2020 · 2020
Cited alongside, same era.
The effect of natural distribution shift on question answering models
John Miller, Karl Krauth, Benjamin Recht, and Ludwig Schmidt. 2020 · 2020
Cited alongside, same era.
GQA: A new dataset for real-world visual reasoning and compositional question answering
Drew A. Hudson and Christopher D. Manning. 2019a
Cited in the paper.
Learning by abstraction: The neural state machine
Drew A. Hudson and Christopher D. Manning. 2019b
Cited in the paper.
Dynaboard: An evaluation-as-a-service platform for holistic next-generation benchmarking
Zhiyi Ma, Kawin Ethayarajh, Tristan Thrush, Somya Jain, Ledell Wu, Robin Jia, Christopher Potts, Adina Williams, and Douwe Kiela. 2021 · 2021
Later among the works it cites.
Accuracy on the line: on the strong correlation between out-of-distribution and in-distribution generalization
John Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, and Ludwig Schmidt. 2021 · 2021
Later among the works it cites.
VinVL: Revisiting visual representations in vision-language models
Pengchuan Zhang, Xiujun Li, Xiaowei Hu, Jianwei Yang, Lei Zhang, Lijuan Wang, Yejin Choi, and Jianfeng Gao. 2021 · 2021
Later among the works it cites.
CARETS: A consistency and robustness evaluative test suite for VQA
Carlos E. Jimenez, Olga Russakovsky, and Karthik Narasimhan. 2022 · 2022
Closest in time.
Winoground: Probing vision and language models for visio-linguistic compositionality
Tristan Thrush, Ryan Jiang, Max Bartolo, Amanpreet Singh, Adina Williams, Douwe Kiela, and Candace Ross. 2022b · 2022
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