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This paper proposes a question-answering (QA) benchmark for spatial reasoning on natural language text which contains more realistic spatial phenomena not covered by prior work and is challenging for state-of-the-art language models (LM).
Ian Tenney, Patrick Xia, Berlin Chen, Alex Wang, Adam Poliak, R Thomas McCoy, Najoung Kim, Benjamin Van Durme, Samuel R Bowman, Dipanjan Das, et al. 2019 · 1905
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UnifiedQA: Crossing format boundaries with a single QA system
Daniel Khashabi, Sewon Min, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter Clark, and Hannaneh Hajishirzi. 2020 · 1907
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Question Answering is a Format; when is it useful?
Matt Gardner, Jonathan Berant, Hannaneh Hajishirzi, Alon Talmor, and Sewon Min. 2019 · 1909
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Geometry and spatial reasoning
Douglas H Clements and Michael T Battista. 1992 · 1992
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
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Foreshadowing the benefits of incidental supervision
Hangfeng He, Mingyuan Zhang, Qiang Ning, and Dan Roth. 2020b · 2006
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Question generation via overgenerating transformations and ranking
Michael Heilman and Noah A Smith. 2009 · 2009
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Distant supervision for relation extraction without labeled data
Mike Mintz, Steven Bills, Rion Snow, and Dan Jurafsky. 2009 · 2009
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Spatial Role Labeling: Task definition and annotation scheme
Parisa Kordjamshidi, Marie-Francine Moens, and Martijn van Otterlo. 2010 · 2010
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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
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Question-Answer Driven Semantic Role Labeling: Using natural language to annotate natural language
Luheng He, Mike Lewis, and Luke Zettlemoyer. 2015 · 2015
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Deep questions without deep understanding
Igor Labutov, Sumit Basu, and Lucy Vanderwende. 2015 · 2015
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Towards ai-complete question answering: A set of prerequisite toy tasks
Jason Weston, Antoine Bordes, Sumit Chopra, Alexander M Rush, Bart van Merriënboer, Armand Joulin, and Tomas Mikolov. 2015 · 2015
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Distant supervision for relation extraction via piecewise convolutional neural networks
Daojian Zeng, Kang Liu, Yubo Chen, and Jun Zhao. 2015 · 2015
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SQuAD: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Learning to Ask: Neural question generation for reading comprehension
Xinya Du, Junru Shao, and Claire Cardie. 2017 · 2017
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Learning to compose spatial relations with grounded neural language models
Mehdi Ghanimifard and Simon Dobnik. 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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A review of spatial reasoning and interaction for real-world robotics
Christian Landsiedel, Verena Rieser, Matthew Walter, and Dirk Wollherr. 2017 · 2017
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Zero-Shot relation extraction via reading comprehension
Omer Levy, Minjoon Seo, Eunsol Choi, and Luke Zettlemoyer. 2017 · 2017
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Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár. 2017 · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 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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Vision-and-language navigation: Interpreting visually-grounded navigation instructions in real environments
GeoSQA: A benchmark for scenario-based question answering in the geography domain at high school level
Zixian Huang, Yulin Shen, Xiao Li, Yu’ang Wei, Gong Cheng, Lin Zhou, Xinyu Dai, and Yuzhong Qu. 2019 · 2019
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GQA: A new dataset for real-world visual reasoning and compositional question answering
Drew A Hudson and Christopher D Manning. 2019 · 2019
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Natural Questions: a benchmark for question answering research
Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob Devlin, Kenton Lee, et al. 2019 · 2019
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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
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XLNet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Russ R Salakhutdinov, and Quoc V Le. 2019 · 2019
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Peter Anderson, Qi Wu, Damien Teney, Jake Bruce, Mark Johnson, Niko Sünderhauf, Ian Reid, Stephen Gould, and Anton van den Hengel. 2018 · 2018
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TempQuestions: A benchmark for temporal question answering
Zhen Jia, Abdalghani Abujabal, Rishiraj Saha Roy, Jannik Strötgen, and Gerhard Weikum. 2018 · 2018
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Looking Beyond the Surface:a challenge set for reading comprehension over multiple sentences
Daniel Khashabi, Snigdha Chaturvedi, Michael Roth, Shyam Upadhyay, and Dan Roth. 2018 · 2018
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Crowdsourcing question-answer meaning representations
Julian Michael, Gabriel Stanovsky, Luheng He, Ido Dagan, and Luke Zettlemoyer. 2018 · 2018
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Sentence encoders on stilts: Supplementary training on intermediate labeled-data tasks
Jason Phang, Thibault Févry, and Samuel R Bowman. 2018 · 2018
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Visually guided spatial relation extraction from text
Taher Rahgooy, Umar Manzoor, and Parisa Kordjamshidi. 2018 · 2018
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GLUE: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel Bowman. 2018 · 2018
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From spatial relations to spatial configurations
Soham Dan, Parisa Kordjamshidi, Julia Bonn, Archna Bhatia, Zheng Cai, Martha Palmer, and Dan Roth. 2020 · 2020
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A hybrid deep learning approach for spatial trigger extraction from radiology reports
Surabhi Datta and Kirk Roberts. 2020 · 2020
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Syn-QG: Syntactic and shallow semantic rules for question generation
Kaustubh Dhole and Christopher D. Manning. 2020 · 2020
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Event extraction by answering (almost) natural questions
Xinya Du and Claire Cardie. 2020 · 2020
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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
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Don’t Stop Pretraining: Adapt language models to domains and tasks
Suchin Gururangan, Ana Marasović, Swabha Swayamdipta, Kyle Lo, Iz Beltagy, Doug Downey, and Noah A. Smith. 2020 · 2020
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ArraMon: A joint navigation-assembly instruction interpretation task in dynamic environments
Hyounghun Kim, Abhaysinh Zala, Graham Burri, Hao Tan, and Mohit Bansal. 2020 · 2020
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ALBERT: A lite bert for self-supervised learning of language representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2020 · 2020
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TORQUE: A reading comprehension dataset of temporal ordering questions
Qiang Ning, Hao Wu, Rujun Han, Nanyun Peng, Matt Gardner, and Dan Roth. 2020 · 2020
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RMM: A recursive mental model for dialogue navigation
Homero Roman Roman, Yonatan Bisk, Jesse Thomason, Asli Celikyilmaz, and Jianfeng Gao. 2020 · 2020
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What do models learn from question answering datasets?
Priyanka Sen and Amir Saffari. 2020 · 2020
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A linguistic analysis of visually grounded dialogues based on spatial expressions
Takuma Udagawa, Takato Yamazaki, and Akiko Aizawa. 2020 · 2020
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Temporal common sense acquisition with minimal supervision
Ben Zhou, Qiang Ning, Daniel Khashabi, and Dan Roth. 2020 · 2020
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