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Asking good questions is an essential ability for both human and machine intelligence.
Unified language model pre-training for natural language understanding and generation
Li Dong, Nan Yang, Wenhui Wang, Furu Wei, Xiaodong Liu, Yu Wang, Jianfeng Gao, Ming Zhou, and Hsiao-Wuen Hon. 2019a · 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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MRQA 2019 shared task: Evaluating generalization in reading comprehension
Adam Fisch, Alon Talmor, Robin Jia, Minjoon Seo, Eunsol Choi, and Danqi Chen. 2019 · 1910
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Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2019 · 1910
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PEGASUS: pre-training with extracted gap-sentences for abstractive summarization
Jingqing Zhang, Yao Zhao, Mohammad Saleh, and Peter J. Liu. 2019 · 1912
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Prophetnet: Predicting future n-gram for sequence-to-sequence pre-training
Yu Yan, Weizhen Qi, Yeyun Gong, Dayiheng Liu, Nan Duan, Jiusheng Chen, Ruofei Zhang, and Ming Zhou. 2020a · 2001
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Prophetnet: Predicting future n-gram for sequence-to-sequence pre-training
Yu Yan, Weizhen Qi, Yeyun Gong, Dayiheng Liu, Nan Duan, Jiusheng Chen, Ruofei Zhang, and Ming Zhou. 2020b · 2001
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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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ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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METEOR: An automatic metric for MT evaluation with improved correlation with human judgments
Satanjeev Banerjee and Alon Lavie. 2005 · 2005
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Good question! statistical ranking for question generation
Michael Heilman and Noah A. Smith. 2010 · 2010
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MCTest: A challenge dataset for the open-domain machine comprehension of text
Matthew Richardson, Christopher J.C. Burges, and Erin Renshaw. 2013 · 2013
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Deep questions without deep understanding
Igor Labutov, Sumit Basu, and Lucy Vanderwende. 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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Question generation for question answering
Nan Duan, Duyu Tang, Peng Chen, and Ming Zhou. 2017 · 2017
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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
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TriviaQA: A large scale distantly supervised challenge dataset for reading comprehension
Mandar Joshi, Eunsol Choi, Daniel Weld, and Luke Zettlemoyer. 2017 · 2017
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Fixing weight decay regularization in adam
Ilya Loshchilov and Frank Hutter. 2017 · 2017
Cited alongside, same era.
NewsQA: A machine comprehension dataset
Adam Trischler, Tong Wang, Xingdi Yuan, Justin Harris, Alessandro Sordoni, Philip Bachman, and Kaheer Suleman. 2017 · 2017
Cited alongside, same era.
Learningq: a large-scale dataset for educational question generation
Guanliang Chen, Jie Yang, Claudia Hauff, and Geert-Jan Houben. 2018 · 2018
Cited alongside, same era.
Automatic question generation using relative pronouns and adverbs
Payal Khullar, Konigari Rachna, Mukul Hase, and Manish Shrivastava. 2018 · 2018
Cited alongside, same era.
The NarrativeQA reading comprehension challenge
Tomáš Kočiský, Jonathan Schwarz, Phil Blunsom, Chris Dyer, Karl Moritz Hermann, Gábor Melis, and Edward Grefenstette. 2018 · 2018
Cited alongside, same era.
TWEETQA: A social media focused question answering dataset
Wenhan Xiong, Jiawei Wu, Hong Wang, Vivek Kulkarni, Mo Yu, Shiyu Chang, Xiaoxiao Guo, and William Yang Wang. 2019 · 2019
Later among the works it cites.
Addressing semantic drift in question generation for semi-supervised question answering
Shiyue Zhang and Mohit Bansal. 2019 · 2019
Later among the works it cites.
Question-type driven question generation
Wenjie Zhou, Minghua Zhang, and Yunfang Wu. 2019 · 2019
Later among the works it cites.
What’s the latest? a question-driven news chatbot
Philippe Laban, John Canny, and Marti A Hearst. 2020 · 2020
Later among the works it cites.
ProphetNet: Predicting future n-gram for sequence-to-SequencePre-training
Weizhen Qi, Yu Yan, Yeyun Gong, Dayiheng Liu, Nan Duan, Jiusheng Chen, Ruofei Zhang, and Ming Zhou. 2020 · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Preksha Nema and Mitesh M Khapra. 2018 · 2018
Cited alongside, same era.
Answer-focused and position-aware neural question generation
Xingwu Sun, Jing Liu, Yajuan Lyu, Wei He, Yanjun Ma, and Shi Wang. 2018 · 2018
Cited alongside, same era.
Learning to ask questions in open-domain conversational systems with typed decoders
Yansen Wang, Chenyi Liu, Minlie Huang, and Liqiang Nie. 2018 · 2018
Cited alongside, same era.
HotpotQA: A dataset for diverse, explainable multi-hop question answering
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William Cohen, Ruslan Salakhutdinov, and Christopher D. Manning. 2018 · 2018
Cited alongside, same era.
A recurrent BERT-based model for question generation
Ying-Hong Chan and Yao-Chung Fan. 2019 · 2019
Cited alongside, same era.
BoolQ: Exploring the surprising difficulty of natural yes/no questions
Christopher Clark, Kenton Lee, Ming-Wei Chang, Tom Kwiatkowski, Michael Collins, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Quoref: A reading comprehension dataset with questions requiring coreferential reasoning
Pradeep Dasigi, Nelson F. Liu, Ana Marasović, Noah A. Smith, and Matt Gardner. 2019 · 2019
Cited alongside, same era.
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
Later among the works it cites.
Multi-hop question generation with graph convolutional network
Dan Su, Yan Xu, Wenliang Dai, Ziwei Ji, Tiezheng Yu, and Pascale Fung. 2020 · 2020
Later among the works it cites.
Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
Later among the works it cites.
Bertscore: Evaluating text generation with BERT
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, and Yoav Artzi. 2020 · 2020
Later among the works it cites.
Controllable open-ended question generation with A new question type ontology
Shuyang Cao and Lu Wang. 2021 · 2021
Closest in time.
Contrastive multi-document question generation
Woon Sang Cho, Yizhe Zhang, Sudha Rao, Asli Celikyilmaz, Chenyan Xiong, Jianfeng Gao, Mengdi Wang, and Bill Dolan. 2021 · 2021
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GooAQ: Open question answering with diverse answer types
Daniel Khashabi, Amos Ng, Tushar Khot, Ashish Sabharwal, Hannaneh Hajishirzi, and Chris Callison-Burch. 2021 · 2021
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Quiz-Style Question Generation for News Stories
Adam D. Lelkes, Vinh Q. Tran, and Cong Yu. 2021 · 2021
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Zero-shot fact verification by claim generation
Liangming Pan, Wenhu Chen, Wenhan Xiong, Min-Yen Kan, and William Yang Wang. 2021 · 2021
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Data-questeval: A referenceless metric for data to text semantic evaluation
Clément Rebuffel, Thomas Scialom, Laure Soulier, Benjamin Piwowarski, Sylvain Lamprier, Jacopo Staiano, Geoffrey Scoutheeten, and Patrick Gallinari. 2021 · 2021
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Automatically generating cause-and-effect questions from passages
Katherine Stasaski, Manav Rathod, Tony Tu, Yunfang Xiao, and Marti A. Hearst. 2021 · 2021
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Qaconv: Question answering on informative conversations
Chien-Sheng Wu, Andrea Madotto, Wenhao Liu, Pascale Fung, and Caiming Xiong. 2021 · 2021
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