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Automatic math problem solving has recently attracted increasing attention as a long-standing AI benchmark.
Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks
Jiasen Lu, Dhruv Batra, Devi Parikh, and Stefan Lee. 2019 · 1908
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Herbert Gelernter, James R Hansen, and Donald W Loveland. 1960 · 1960
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Basic principles of mechanical theorem proving in elementary geometries
Wu Wen-Tsun. 1986 · 1986
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Automated generation of readable proofs with geometric invariants
Shang-Ching Chou, Xiao-Shan Gao, and Jing-Zhong Zhang. 1996 · 1996
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
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An introduction to java geometry expert
Zheng Ye, Shang-Ching Chou, and Xiao-Shan Gao. 2008 · 2008
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Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014 · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
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Learning to automatically solve algebra word problems
Nate Kushman, Yoav Artzi, Luke Zettlemoyer, and Regina Barzilay. 2014 · 2014
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Diagram understanding in geometry questions
Min Joon Seo, Hannaneh Hajishirzi, Ali Farhadi, and Oren Etzioni. 2014 · 2014
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Solving geometry problems: Combining text and diagram interpretation
Minjoon Seo, Hannaneh Hajishirzi, Ali Farhadi, Oren Etzioni, and Clint Malcolm. 2015a · 2015
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Solving geometry problems: Combining text and diagram interpretation
Minjoon Seo, Hannaneh Hajishirzi, Ali Farhadi, Oren Etzioni, and Clint Malcolm. 2015b · 2015
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Learn to solve algebra word problems using quadratic programming
Lipu Zhou, Shuaixiang Dai, and Liwei Chen. 2015 · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
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How well do computers solve math word problems? large-scale dataset construction and evaluation
Danqing Huang, Shuming Shi, Chin-Yew Lin, Jian Yin, and Wei-Ying Ma. 2016 · 2016
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Unsupervised learning of visual representations by solving jigsaw puzzles
Mehdi Noroozi and Paolo Favaro. 2016 · 2016
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Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell, and Alexei A Efros. 2016 · 2016
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Yash Goyal, Tejas Khot, Douglas Summers-Stay, Dhruv Batra, and Devi Parikh. 2017 · 2017
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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 Girshick. 2017 · 2017
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Translating a math word problem to a expression tree
Lei Wang, Yan Wang, Deng Cai, Dongxiang Zhang, and Xiaojiang Liu. 2018 · 2018
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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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Unaiza Ahsan, Rishi Madhok, and Irfan Essa. 2019 · 2019
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Mathqa: Towards interpretable math word problem solving with operation-based formalisms
Aida Amini, Saadia Gabriel, Peter Lin, Rik Koncel-Kedziorski, Yejin Choi, and Hannaneh Hajishirzi. 2019 · 2019
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Photo-realistic single image super-resolution using a generative adversarial network
Christian Ledig, Lucas Theis, Ferenc Huszár, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, et al. 2017 · 2017
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Automatic differentiation in pytorch
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer. 2017 · 2017
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Film: Visual reasoning with a general conditioning layer
Ethan Perez, Florian Strub, Harm De Vries, Vincent Dumoulin, and Aaron Courville. 2017 · 2017
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From textbooks to knowledge: A case study in harvesting axiomatic knowledge from textbooks to solve geometry problems
Mrinmaya Sachan, Kumar Dubey, and Eric Xing. 2017 · 2017
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Learning to solve geometry problems from natural language demonstrations in textbooks
Mrinmaya Sachan and Eric Xing. 2017 · 2017
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A simple neural network module for relational reasoning
Adam Santoro, David Raposo, David G Barrett, Mateusz Malinowski, Razvan Pascanu, Peter Battaglia, and Timothy Lillicrap. 2017 · 2017
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Deep neural solver for math word problems
Yan Wang, Xiaojiang Liu, and Shuming Shi. 2017 · 2017
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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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A goal-driven tree-structured neural model for math word problems
Zhipeng Xie and Shichao Sun. 2019 · 2019
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Deep modular co-attention networks for visual question answering
Zhou Yu, Jun Yu, Yuhao Cui, Dacheng Tao, and Qi Tian. 2019 · 2019
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Gen Li, Nan Duan, Yuejian Fang, Ming Gong, and Daxin Jiang. 2020 · 2020
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A diverse corpus for evaluating and developing english math word problem solvers
Shen-Yun Miao, Chao-Chun Liang, and Keh-Yih Su. 2020 · 2020
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How useful is self-supervised pretraining for visual tasks?
Alejandro Newell and Jia Deng. 2020 · 2020
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Knowledge graph embedding compression
Mrinmaya Sachan. 2020 · 2020
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Discourse in multimedia: A case study in extracting geometry knowledge from textbooks
Mrinmaya Sachan, Avinava Dubey, Eduard H Hovy, Tom M Mitchell, Dan Roth, and Eric P Xing. 2020 · 2020
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Multi-task self-supervised visual learning
Carl Doersch and Andrew Zisserman. 2017 · 2060
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