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In addition to the traditional task of getting machines to answer questions, a major research question in question answering is to create interesting, challenging questions that can help systems learn how to answer questions and also reveal which systems are the best at answering questions.
Quizbowl: The case for incremental question answering
Pedro Rodriguez, Shi Feng, Mohit Iyyer, He He, and Jordan L. Boyd-Graber. 2019 · 1904
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Xlnet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan Salakhutdinov, and Quoc V. Le. 2019 · 1906
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The fall of Charlie Van Doren
Morris Freedman. 1997 · 1997
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As Long as They’re Laughing: Groucho Marx and You Bet Your Life
R. Dwan. 2000 · 2000
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Building a question answering test collection
Ellen M Voorhees and Dawn M Tice. 2000 · 2000
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BLEU: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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Ethical issues in advanced artificial intelligence
Nick Bostrom. 2003 · 2003
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The Zone of Proximal Development in Vygotsky’s Analysis of Learning and Instruction , Learning in Doing: Social, Cognitive and Computational Perspectives, page 39–64. Cambridge University Press
Seth Chaiklin. 2003 · 2003
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Evaluating the evaluation: A case study using the TREC 2002 question answering track
Ellen M. Voorhees. 2003 · 2003
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Rouge: a package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Games with a purpose
Luis von Ahn. 2006 · 2006
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Brainiac: adventures in the curious, competitive, compulsive world of trivia buffs
Ken Jennings. 2006 · 2006
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Modeling the effects of memory on human online sentence processing with particle filters
Roger P. Levy, Florencia Reali, and Thomas L. Griffiths. 2008 · 2008
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Evaluating Question Answering System Performance , pages 409–430. Springer Netherlands, Dordrecht
Ellen M. Voorhees. 2008 · 2008
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How To Make 100 Pounds A Night (Or More) As A Pub Quizmaster
Paul Diamond. 2009 · 2009
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Building Watson: An Overview of the DeepQA Project
David Ferrucci, Eric Brown, Jennifer Chu-Carroll, James Fan, David Gondek, Aditya A. Kalyanpur, Adam Lally, J. William Murdock, Eric Nyberg, John Prager, Nico Schlaefer, and Chris Welty. 2010 · 2010
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A.: Estimating machine translation post-editing effort with HTER
Lucia Specia and Atefeh Farzindar. 2010 · 2010
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Integrating surprisal and uncertain-input models in online sentence comprehension: formal techniques and empirical results
Roger Levy. 2011 · 2011
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Besting the quiz master: Crowdsourcing incremental classification games
Jordan Boyd-Graber, Brianna Satinoff, He He, and Hal Daume III. 2012 · 2012
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Your starter for ten: 50 years of university challenge
David Taylor, Colin McNulty, and Jo Meek. 2012 · 2012
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Using gamification to inspire new citizen science volunteers
Anne Bowser, Derek Hansen, Yurong He, Carol Boston, Matthew Reid, Logan Gunnell, and Jennifer Preece. 2013 · 2013
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Quizbowl lexicon
Stephen Eltinge. 2013 · 2013
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From query to question in one click: Suggesting synthetic questions to searchers
Idan Szpektor and Gideon Dror. 2013 · 2013
Cited alongside, same era.
Findings of the 2014 workshop on statistical machine translation
Ondřej Bojar, Christian Buck, Christian Federmann, Barry Haddow, Philipp Koehn, Johannes Leveling, Christof Monz, Pavel Pecina, Matt Post, Herve Saint-Amand, Radu Soricut, Lucia Specia, and Aleš Tamchyna. 2014 · 2014
Cited alongside, same era.
Don’t until the final verb wait: Reinforcement learning for simultaneous machine translation
Alvin Grissom II, He He, Jordan Boyd-Graber, and John Morgan. 2014 · 2014
Cited alongside, same era.
Television Game Show Hosts: Biographies of 32 Stars
David Baber. 2015 · 2015
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Why do you ask? good questions provoke informative answers
Robert X. D. Hawkins, Andreas Stuhlmüller, Judith Degen, and Noah D. Goodman. 2015 · 2015
Cited alongside, same era.
Teaching machines to read and comprehend
Know what you don’t know: Unanswerable questions for SQuAD
Pranav Rajpurkar, Robin Jia, and Percy Liang. 2018 · 2018
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Learning to ask good questions: Ranking clarification questions using neural expected value of perfect information
Sudha Rao and Hal Daumé III. 2018 · 2018
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CoQA: A conversational question answering challenge
Siva Reddy, Danqi Chen, and Christopher D. Manning. 2018 · 2018
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Systematic error analysis of the Stanford question answering dataset
Marc-Antoine Rondeau and T. J. Hazen. 2018 · 2018
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What makes reading comprehension questions easier?
Saku Sugawara, Kentaro Inui, Satoshi Sekine, and Akiko Aizawa. 2018 · 2018
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Proceedings of the First Workshop on Fact Extraction and VERification (FEVER) . Association for Computational Linguistics, Brussels, Belgium
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Karl Moritz Hermann, Tomas Kocisky, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom. 2015 · 2015
Cited alongside, same era.
Semantic parsing via staged query graph generation: Question answering with knowledge base
Wen-tau Yih, Ming-Wei Chang, Xiaodong He, and Jianfeng Gao. 2015 · 2015
Cited alongside, same era.
Interactive machine comprehension with information seeking agents
Xingdi Yuan, Jie Fu, Marc-Alexandre Cote, Yi Tay, Christopher Pal, and Adam Trischler. 2019 · 2015
Cited alongside, same era.
Opponent modeling in deep reinforcement learning
He He, Jordan Boyd-Graber, Kevin Kwok, and Hal Daumé III. 2016 · 2016
Cited alongside, same era.
SQuAD: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
Cited alongside, same era.
Build it, break it, fix it: Contesting secure development
Andrew Ruef, Michael Hicks, James Parker, Dave Levin, Michelle L. Mazurek, and Piotr Mardziel. 2016 · 2016
Cited alongside, same era.
SearchQA: A new Q&A dataset augmented with context from a search engine
Matthew Dunn, Levent Sagun, Mike Higgins, V. Ugur Güney, Volkan Cirik, and Kyunghyun Cho. 2017 · 2017
Cited alongside, same era.
James Thorne, Andreas Vlachos, Oana Cocarascu, Christos Christodoulopoulos, and Arpit Mittal, editors. 2018 · 2018
Later among the works it cites.
Show your work: Improved reporting of experimental results
Jesse Dodge, Suchin Gururangan, Dallas Card, Roy Schwartz, and Noah A. Smith. 2019 · 2019
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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
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Can you unpack that? learning to rewrite questions-in-context
Ahmed Elgohary, Denis Peskov, and Jordan Boyd-Graber. 2019 · 2019
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What ai can do for me: Evaluating machine learning interpretations in cooperative play
Shi Feng and Jordan Boyd-Graber. 2019 · 2019
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Proceedings of the 2nd Workshop on Machine Reading for Question Answering . Association for Computational Linguistics, Hong Kong, China
Adam Fisch, Alon Talmor, Robin Jia, Minjoon Seo, Eunsol Choi, and Danqi Chen, editors. 2019 · 2019
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Are we modeling the task or the annotator? an investigation of annotator bias in natural language understanding datasets
Mor Geva, Yoav Goldberg, and Jonathan Berant. 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, Matthew Kelcey, Jacob Devlin, Kenton Lee, Kristina N. Toutanova, Llion Jones, Ming-Wei Chang, Andrew Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov. 2019 · 2019
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Latent retrieval for weakly supervised open domain question answering
Kenton Lee, Ming-Wei Chang, and Kristina Toutanova. 2019 · 2019
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STACL: Simultaneous translation with implicit anticipation and controllable latency using prefix-to-prefix framework
Mingbo Ma, Liang Huang, Hao Xiong, Renjie Zheng, Kaibo Liu, Baigong Zheng, Chuanqiang Zhang, Zhongjun He, Hairong Liu, Xing Li, Hua Wu, and Haifeng Wang. 2019 · 2019
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How uncle Jamie broke jeopardy
Kenny Malone. 2019 · 2019
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Inherent disagreements in human textual inferences
Ellie Pavlick and Tom Kwiatkowski. 2019 · 2019
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Trick me if you can: Human-in-the-loop generation of adversarial question answering examples
Eric Wallace, Pedro Rodriguez, Shi Feng, Ikuya Yamada, and Jordan Boyd-Graber. 2019 · 2019
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Lessons from archives: Strategies for collecting sociocultural data in machine learning
Eun Seo Jo and Timnit Gebru. 2020 · 2020
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A set of recommendations for assessing human–machine parity in language translation
Samuel Laubli, Sheila Castilho, Graham Neubig, Rico Sennrich, Qinlan Shen, and Antonio Toral. 2020 · 2020
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Why control-f is the single most important thing you can teach someone about search
Dan Russell. 2020 · 2020
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Assessing the benchmarking capacity of machine reading comprehension datasets
Saku Sugawara, Pontus Stenetorp, Kentaro Inui, and Akiko Aizawa. 2020 · 2020
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