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Open-domain question answering can be formulated as a phrase retrieval problem, in which we can expect huge scalability and speed benefit but often suffer from low accuracy due to the limitation of existing phrase representation models.
Support-vector networks
Corinna Cortes and Vladimir Vapnik. 1995 · 1995
Earlier work this paper cites.
The trec-8 question answering track report
Ellen M Voorhees et al. 1999 · 1999
Earlier work this paper cites.
Modeling of the question answering task in the yodaqa system
Petr Baudiš and Jan Šedivỳ. 2015 · 2015
Earlier work this paper cites.
Sparse overcomplete word vector representations
Manaal Faruqui, Yulia Tsvetkov, Dani Yogatama, Chris Dyer, and Noah A Smith. 2015 · 2015
Earlier work this paper cites.
Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
Earlier work this paper cites.
Reading wikipedia to answer open-domain questions
Danqi Chen, Adam Fisch, Jason Weston, and Antoine Bordes. 2017 · 2017
Earlier work this paper cites.
Ranking paragraphs for improving answer recall in open-domain question answering
Jinhyuk Lee, Seongjun Yun, Hyunjae Kim, Miyoung Ko, and Jaewoo Kang. 2018 · 2018
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Denoising distantly supervised open-domain question answering
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Anant Subramanian, Danish Pruthi, Harsh Jhamtani, Taylor Berg-Kirkpatrick, and Eduard Hovy. 2018 · 2018
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Shuohang Wang, Mo Yu, Xiaoxiao Guo, Zhiguo Wang, Tim Klinger, Wei Zhang, Shiyu Chang, Gerry Tesauro, Bowen Zhou, and Jing Jiang. 2018 · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 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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Real-time open-domain question answering with dense-sparse phrase index
Minjoon Seo, Jinhyuk Lee, Tom Kwiatkowski, Ankur P Parikh, Ali Farhadi, and Hannaneh Hajishirzi. 2019 · 2019
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Multi-passage bert: A globally normalized bert model for open-domain question answering
Zhiguo Wang, Patrick Ng, Xiaofei Ma, Ramesh Nallapati, and Bing Xiang. 2019 · 2019
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End-to-end open-domain question answering with bertserini
Wei Yang, Yuqing Xie, Aileen Lin, Xingyu Li, Luchen Tan, Kun Xiong, Ming Li, and Jimmy Lin. 2019 · 2019
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Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, and Andrew McCallum. 2019 · 2019
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