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Machine Reading Comprehension (MRC) is a challenging Natural Language Processing(NLP) research field with wide real-world applications.
A Survey on Neural Machine Reading Comprehension
Qiu, B.; Chen, X.; Xu, J.; Sun, Y · 1906
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Multi-Passage Machine Reading Comprehension with Cross-Passage Answer Verification
Wang, Y.; Liu, K.; Liu, J.; He, W.; Lyu, Y.; Wu, H.; Li, S.; Wang, H · 1927
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Project gutenberg, 1971
Hart, M · 1971
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Derivation of new readability formulas (automated readability index, fog count and flesch reading ease formula) for navy enlisted personnel 1975
Kincaid, J.P.; Fishburne Jr, R.P.; Rogers, R.L.; Chissom, B.S · 1975
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The language of thought
Fodor, J.A · 1975
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The Process of Question Answering
Lehnert, W.G · 1977
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Theories of semantic memory
Smith, E.E · 1978
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Information retrieval 1979
Van Rijsbergen, C.J · 1979
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Computation and cognition
Pylyshyn, Z.W · 1984
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Deep Read: A Reading Comprehension System
Hirschman, L.; Light, M.; Breck, E.; Burger, J.D · 1999
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Perceptual symbol systems
Barsalou, L.W · 1999
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A Rule-Based Question Answering System for Reading Comprehension Tests
Riloff, E.; Thelen, M · 2000
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Reading Comprehension Programs in a Statistical-Language-Processing Class
Charniak, E.; Altun, Y.; de Salvo Braz, R.; Garrett, B.; Kosmala, M.; Moscovich, T.; Pang, L.; Pyo, C.; Sun, Y.; Wy, W.; Yang, Z.; Zeiler, S.; Zorn, L · 2000
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Bleu: a Method for Automatic Evaluation of Machine Translation
Papineni, K.; Roukos, S.; Ward, T.; Zhu, W.J · 2002
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English gigaword
Graff, D.; Kong, J.; Chen, K.; Maeda, K · 2003
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Deep Learning Based Text Classification: A Comprehensive Review, 2020, [arXiv:cs.CL/2004.03705]
Minaee, S.; Kalchbrenner, N.; Cambria, E.; Nikzad, N.; Chenaghlu, M.; Gao, J · 2004
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ROUGE: A Package for Automatic Evaluation of Summaries
Lin, C.Y · 2004
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METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments
Banerjee, S.; Lavie, A · 2005
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Grounding cognition: The role of perception and action in memory, language, and thinking
Pecher, D.; Zwaan, R.A · 2005
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Embodiment and cognitive science
Gibbs Jr, R.W · 2005
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Answering and Questioning for Machine Reading
Vanderwende, L · 2007
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Grounded cognition
Barsalou, L.W · 2008
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Embodied grounding: Social, cognitive, affective, and neuroscientific approaches
Semin, G.R.; Smith, E.R · 2008
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The clueweb09 dataset, 2009, 2009
Callan, J.; Hoy, M.; Yoo, C.; Zhao, L · 2009
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METEOR-NEXT and the METEOR Paraphrase Tables: Improved Evaluation Support for Five Target Languages
Denkowski, M.; Lavie, A · 2010
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Meteor 1.3: Automatic Metric for Reliable Optimization and Evaluation of Machine Translation Systems
Denkowski, M.; Lavie, A · 2011
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A survey of crowdsourcing systems
Yuen, M.C.; King, I.; Leung, K.S · 2011
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MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of Text
Richardson, M.; Burges, C.J.; Renshaw, E · 2013
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Cognitive neuroscience of language
Kemmerer, D · 2014
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Machine comprehension with syntax, frames, and semantics
Wang, H.; Bansal, M.; Gimpel, K.; McAllester, D · 2015
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Learning answer-entailing structures for machine comprehension
Sachan, M.; Dubey, K.; Xing, E.; Richardson, M · 2015
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Machine comprehension with discourse relations
Narasimhan, K.; Barzilay, R · 2015
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Teaching machines to read and comprehend
Hermann, K.M.; Kocisky, T.; Grefenstette, E.; Espeholt, L.; Kay, W.; Suleyman, M.; Blunsom, P · 2015
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Teaching machines to read and comprehend
Hermann, K.M.; Kocisky, T.; Grefenstette, E.; Espeholt, L.; Kay, W.; Suleyman, M.; Blunsom, P · 2015
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Modeling of the question answering task in the yodaqa system
Baudiš, P.; Šedivỳ, J · 2015
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A large annotated corpus for learning natural language inference
Bowman, S.R.; Angeli, G.; Potts, C.; Manning, C.D · 2015
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Vqa: Visual question answering
Antol, S.; Agrawal, A.; Lu, J.; Mitchell, M.; Batra, D.; Lawrence Zitnick, C.; Parikh, D · 2015
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Reading pictures for story comprehension requires mental imagery skills
Boerma, I.E.; Mol, S.E.; Jolles, J · 2016
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Squad: 100,000+ questions for machine comprehension of text
Rajpurkar, P.; Zhang, J.; Lopyrev, K.; Liang, P · 2016
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Bidirectional attention flow for machine comprehension
Seo, M.; Kembhavi, A.; Farhadi, A.; Hajishirzi, H · 2016
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The Goldilocks Principle: Reading Children’s Books with Explicit Memory Representations
Hill, F.; Bordes, A.; Chopra, S.; Weston, J · 2016
Cited alongside, same era.
Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks
Weston, J.; Bordes, A.; Chopra, S.; Mikolov, T · 2016
Cited alongside, same era.
Movieqa: Understanding stories in movies through question-answering
Tapaswi, M.; Zhu, Y.; Stiefelhagen, R.; Torralba, A.; Urtasun, R.; Fidler, S · 2016
Cited alongside, same era.
MS MARCO: A Human Generated MAchine Reading COmprehension Dataset
Nguyen, T.; Rosenberg, M.; Song, X.; Gao, J.; Tiwary, S.; Majumder, R.; Deng, L · 2016
Cited alongside, same era.
Who did What: A Large-Scale Person-Centered Cloze Dataset
Onishi, T.; Wang, H.; Bansal, M.; Gimpel, K.; McAllester, D · 2016
Cited alongside, same era.
QuAC: Question Answering in Context
Choi, E.; He, H.; Iyyer, M.; Yatskar, M.; Yih, W.t.; Choi, Y.; Liang, P.; Zettlemoyer, L · 2018
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HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
Yang, Z.; Qi, P.; Zhang, S.; Bengio, Y.; Cohen, W.; Salakhutdinov, R.; Manning, C.D · 2018
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DuoRC: Towards Complex Language Understanding with Paraphrased Reading Comprehension
Saha, A.; Aralikatte, R.; Khapra, M.M.; Sankaranarayanan, K · 2018
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Large-scale Cloze Test Dataset Created by Teachers
Xie, Q.; Lai, G.; Dai, Z.; Hovy, E · 2018
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Record: Bridging the gap between human and machine commonsense reading comprehension
Zhang, S.; Liu, X.; Liu, J.; Gao, J.; Duh, K.; Van Durme, B · 2018
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Key-Value Memory Networks for Directly Reading Documents (EMNLP16) 2016
Miller, A.H.; Fisch, A.; Dodge, J.; Karimi, A.H.; Bordes, A.; Weston, J · 2016
Cited alongside, same era.
The LAMBADA dataset: word prediction requiring a broad discourse context
Boleda, G.; Paperno, D.; Kruszewski, G.; Lazaridou, A.; Pham, Q.N.; Bernardi, R.; Pezzelle, S.; Baroni, M.; Fernandez, R · 2016
Cited alongside, same era.
WikiReading: A Novel Large-scale Language Understanding Task over Wikipedia
Hewlett, D.; Lacoste, A.; Jones, L.; Polosukhin, I.; Fandrianto, A.; Han, J.; Kelcey, M.; Berthelot, D · 2016
Cited alongside, same era.
Embracing data abundance: Booktest dataset for reading comprehension
Bajgar, O.; Kadlec, R.; Kleindienst, J · 2016
Cited alongside, same era.
Building Large Machine Reading-Comprehension Datasets using Paragraph Vectors
Soricut, R.; Ding, N · 2016
Cited alongside, same era.
An analysis of prerequisite skills for reading comprehension
Sugawara, S.; Aizawa, A · 2016
Cited alongside, same era.
Are you smarter than a sixth grader? textbook question answering for multimodal machine comprehension
Kembhavi, A.; Seo, M.; Schwenk, D.; Choi, J.; Farhadi, A.; Hajishirzi, H · 2017
Cited alongside, same era.
Šuster, S.; Daelemans, W · 2018
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Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
Clark, P.; Cowhey, I.; Etzioni, O.; Khot, T.; Sabharwal, A.; Schoenick, C.; Tafjord, O · 2018
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Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering
Mihaylov, T.; Clark, P.; Khot, T.; Sabharwal, A · 2018
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Scitail: A textual entailment dataset from science question answering
Khot, T.; Sabharwal, A.; Clark, P · 2018
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Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences
Khashabi, D.; Chaturvedi, S.; Roth, M.; Upadhyay, S.; Roth, D · 2018
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Learning to Read Academic Papers 2018
Hong, Y.; Wang, J.; Zhang, X.; Wu, Z · 2018
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MCScript: A Novel Dataset for Assessing Machine Comprehension Using Script Knowledge
Ostermann, S.; Modi, A.; Roth, M.; Thater, S.; Pinkal, M · 2018
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Tracking State Changes in Procedural Text: a Challenge Dataset and Models for Process Paragraph Comprehension
Dalvi, B.; Huang, L.; Tandon, N.; Yih, W.t.; Clark, P · 2018
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Weaver: Deep co-encoding of questions and documents for machine reading
Raison, M.; Mazaré, P.E.; Das, R.; Bordes, A · 2018
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Assessing the Benchmarking Capacity of Machine Reading Comprehension Datasets
Sugawara, S.; Stenetorp, P.; Inui, K.; Aizawa, A · 2019
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Machine reading comprehension: a literature review
Zhang, X.; Yang, A.; Li, S.; Wang, Y · 2019
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Roberta: A robustly optimized bert pretraining approach
Liu, Y.; Ott, M.; Goyal, N.; Du, J.; Joshi, M.; Chen, D.; Levy, O.; Lewis, M.; Zettlemoyer, L.; Stoyanov, V · 2019
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Xlnet: Generalized autoregressive pretraining for language understanding
Yang, Z.; Dai, Z.; Yang, Y.; Carbonell, J.; Salakhutdinov, R.R.; Le, Q.V · 2019
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Neural machine reading comprehension: Methods and trends
Liu, S.; Zhang, X.; Zhang, S.; Wang, H.; Zhang, W · 2019
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Research on Machine Reading Comprehension and Textual Question Answering
Hu, M · 2019
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Coqa: A conversational question answering challenge
Reddy, S.; Chen, D.; Manning, C.D · 2019
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DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs
Dua, D.; Wang, Y.; Dasigi, P.; Stanovsky, G.; Singh, S.; Gardner, M · 2019
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Can Machines Learn to Comprehend Scientific Literature?
Park, D.; Choi, Y.; Kim, D.; Yu, M.; Kim, S.; Kang, J · 2019
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Natural questions: a benchmark for question answering research
Kwiatkowski, T.; Palomaki, J.; Redfield, O.; Collins, M.; Parikh, A.; Alberti, C.; Epstein, D.; Polosukhin, I.; Devlin, J.; Lee, K.; others · 2019
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Dream: A challenge data set and models for dialogue-based reading comprehension
Sun, K.; Yu, D.; Chen, J.; Yu, D.; Choi, Y.; Cardie, C · 2019
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CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge
Talmor, A.; Herzig, J.; Lourie, N.; Berant, J · 2019
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Can Machines Learn to Comprehend Scientific Literature?
Park, D.; Choi, Y.; Kim, D.; Yu, M.; Kim, S.; Kang, J · 2019
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A deep cascade model for multi-document reading comprehension
Yan, M.; Xia, J.; Wu, C.; Bi, B.; Zhao, Z.; Zhang, J.; Si, L.; Wang, R.; Wang, W.; Chen, H · 2019
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Embodied cognition
Shapiro, L · 2019
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Storks, S.; Gao, Q.; Chai, J.Y · 2019
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Measuring text readability with machine comprehension: a pilot study
Benzahra, M.; Yvon, F · 2019
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The understanding problem in cognitive science
Hough, A.R.; Gluck, K · 2019
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A Survey on Machine Reading Comprehension Systems
Baradaran, R.; Ghiasi, R.; Amirkhani, H · 2020
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Conversational Machine Comprehension: a Literature Review
Gupta, S.; Rawat, B.P.S · 2020
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SG-Net: Syntax-Guided Machine Reading Comprehension
Zhang, Z.; Wu, Y.; Zhou, J.; Duan, S.; Wang, R · 2020
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Toward Human-Level Knowledge Representation with a Natural Language of Thought 2020
Jackson Jr, P.C · 2020
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Two Forms of Knowledge Representations in the Human Brain
Wang, X.; Men, W.; Gao, J.; Caramazza, A.; Bi, Y · 2020
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Adversarial Examples for Evaluating Reading Comprehension Systems
Jia, R.; Liang, P · 2031
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Interpretation of Natural Language Rules in Conversational Machine Reading
Saeidi, M.; Bartolo, M.; Lewis, P.; Singh, S.; Rocktäschel, T.; Sheldon, M.; Bouchard, G.; Riedel, S · 2097
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