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We propose an end-to-end approach for synthetic QA data generation.
The curious case of neural text degeneration
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Exploring the limits of transfer learning with a unified text-to-text transformer
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Huggingface’s transformers: State-of-the-art natural language processing
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Computer-aided generation of multiple-choice tests
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The first question generation shared task evaluation challenge
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Teaching machines to read and comprehend
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An overview of the bioasq large-scale biomedical semantic indexing and question answering competition
George Tsatsaronis, Georgios Balikas, Prodromos Malakasiotis, Ioannis Partalas, Matthias Zschunke, Michael R Alvers, Dirk Weissenborn, Anastasia Krithara, Sergios Petridis, Dimitris Polychronopoulos, Yannis Almirantis, John Pavlopoulos, Nicolas Baskiotis, Patrick Gallinari, Thierry Artieres, Axel Ngonga, Norman Heino, Eric Gaussier, Liliana Barrio-Alvers, Michael Schroeder, Ion Androutsopoulos, and Georgios Paliouras. 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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Fixing weight decay regularization in adam
Ilya Loshchilov and Frank Hutter. 2017 · 2017
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Question answering and question generation as dual tasks
Duyu Tang, Nan Duan, Tao Qin, Zhao Yan, and Ming Zhou. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
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Self-training for jointly learning to ask and answer questions
Mrinmaya Sachan and Eric Xing. 2018 · 2018
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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, Kristina Toutanova, Llion Jones, Matthew Kelcey, Ming-Wei Chang, Andrew M. Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov. 2019 · 2019
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Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer. 2019 · 2019
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Unsupervised domain adaptation of language models for reading comprehension
Kosuke Nishida, Kyosuke Nishida, Itsumi Saito, Hisako Asano, and Junji Tomita. 2019 · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al. 2019 · 2019
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DuoRC: Towards Complex Language Understanding with Paraphrased Reading Comprehension
Amrita Saha, Rahul Aralikatte, Mitesh M. Khapra, and Karthik Sankaranarayanan. 2018 · 2018
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Leveraging context information for natural question generation
Linfeng Song, Zhiguo Wang, Wael Hamza, Yue Zhang, and Daniel Gildea. 2018 · 2018
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Answer-focused and position-aware neural question generation
Xingwu Sun, Jing Liu, Yajuan Lyu, Wei He, Yanjun Ma, and Shi Wang. 2018 · 2018
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Paragraph-level neural question generation with maxout pointer and gated self-attention networks
Yao Zhao, Xiaochuan Ni, Yuanyuan Ding, and Qifa Ke. 2018 · 2018
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Synthetic QA corpora generation with roundtrip consistency
Chris Alberti, Daniel Andor, Emily Pitler, Jacob Devlin, and Michael Collins. 2019 · 2019
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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 · 2019
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Putting the horse before the cart: A generator-evaluator framework for question generation from text
Vishwajeet Kumar, Ganesh Ramakrishnan, and Yuan-Fang Li. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
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Capturing greater context for question generation
Luu Anh Tuan, Darsh J Shah, and Regina Barzilay. 2019 · 2019
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Towards a human-like open-domain chatbot
Daniel Adiwardana, Minh-Thang Luong, David R. So, Jamie Hall, Noah Fiedel, Romal Thoppilan, Zi Yang, Apoorv Kulshreshtha, Gaurav Nemade, Yifeng Lu, and Quoc V. Le. 2020 · 2020
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Reinforcement learning based graph-to-sequence model for natural question generation
Yu Chen, Lingfei Wu, and Mohammed J. Zaki. 2020 · 2020
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Dong Bok Lee, Seanie Lee, Woo Tae Jeong, Donghwan Kim, and Sung Ju Hwang. 2020 · 2020
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Improving question generation with sentence-level semantic matching and answer position inferring
Xiyao Ma, Qile Zhu, Yanlin Zhou, and Xiaolin Li. 2020 · 2020
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Training question answering models from synthetic data
Raul Puri, Ryan Spring, Mostofa Patwary, Mohammad Shoeybi, and Bryan Catanzaro. 2020 · 2020
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Neural question generation with answer pivot
Xiaochuan Wang, Bingning Wang, Ting Yao, Qi Zhang, and Jingfang Xu. 2020 · 2020
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