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Fusion-in-decoder (Fid) (Izacard and Grave, 2020) is a generative question answering (QA) model that leverages passage retrieval with a pre-trained transformer and pushed the state of the art on single-hop QA.
ELI5: long form question answering
Angela Fan, Yacine Jernite, Ethan Perez, David Grangier, Jason Weston, and Michael Auli. 2019 · 1907
Earlier work this paper cites.
Multi-hop question answering via reasoning chains
Jifan Chen, Shih-Ting Lin, and Greg Durrett. 2019 · 1910
Earlier work this paper cites.
Neural assistant: Joint action prediction, response generation, and latent knowledge reasoning
Arvind Neelakantan, Semih Yavuz, Sharan Narang, Vishaal Prasad, Ben Goodrich, Daniel Duckworth, Chinnadhurai Sankar, and Xifeng Yan. 2019 · 1910
Earlier work this paper cites.
Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, and Jamie Brew. 2019 · 1910
Earlier work this paper cites.
The trec-8 question answering track report
Ellen M. Voorhees. 1999 · 1999
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Andre Esteva, Anuprit Kale, Romain Paulus, Kazuma Hashimoto, Wenpeng Yin, Dragomir R. Radev, and Richard Socher. 2020 · 2006
Earlier work this paper cites.
Hopretriever: Retrieve hops over wikipedia to answer complex questions
Shaobo Li, Xiaoguang Li, Lifeng Shang, Xin Jiang, Qun Liu, Chengjie Sun, Zhenzhou Ji, and Bingquan Liu. 2020 · 2012
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
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Reading Wikipedia to answer open-domain questions
Danqi Chen, Adam Fisch, Jason Weston, and Antoine Bordes. 2017 · 2017
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Accurate supervised and semi-supervised machine reading for long documents
Daniel Hewlett, Llion Jones, Alexandre Lacoste, and Izzeddin Gur. 2017 · 2017
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Simple and effective multi-paragraph reading comprehension
Christopher Clark and Matt Gardner. 2018 · 2018
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The web as a knowledge-base for answering complex questions
Alon Talmor and Jonathan Berant. 2018 · 2018
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Constructing datasets for multi-hop reading comprehension across documents
Johannes Welbl, Pontus Stenetorp, and Sebastian Riedel. 2018 · 2018
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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
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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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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
Cited alongside, same era.
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
Cited alongside, same era.
Latent retrieval for weakly supervised open domain question answering
Kenton Lee, Ming-Wei Chang, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
A discrete hard EM approach for weakly supervised question answering
Sewon Min, Danqi Chen, Hannaneh Hajishirzi, and Luke Zettlemoyer. 2019 · 2019
Cited alongside, same era.
Revealing the importance of semantic retrieval for machine reading at scale
Yixin Nie, Songhe Wang, and Mohit Bansal. 2019 · 2019
Cited alongside, same era.
Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
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AmbigQA: Answering ambiguous open-domain questions
Sewon Min, Julian Michael, Hannaneh Hajishirzi, and Luke Zettlemoyer. 2020 · 2020
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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
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How much knowledge can you pack into the parameters of a language model?
Adam Roberts, Colin Raffel, and Noam Shazeer. 2020 · 2020
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Select, answer and explain: Interpretable multi-hop reading comprehension over multiple documents
Ming Tu, Kevin Huang, Guangtao Wang, Jing Huang, Xiaodong He, and Bowen Zhou. 2020 · 2020
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Answering while summarizing: Multi-task learning for multi-hop QA with evidence extraction
Kosuke Nishida, Kyosuke Nishida, Masaaki Nagata, Atsushi Otsuka, Itsumi Saito, Hisako Asano, and Junji Tomita. 2019 · 2019
Cited alongside, same era.
Answering complex open-domain questions through iterative query generation
Peng Qi, Xiaowen Lin, Leo Mehr, Zijian Wang, and Christopher D. Manning. 2019 · 2019
Cited alongside, same era.
Dynamically fused graph network for multi-hop reasoning
Lin Qiu, Yunxuan Xiao, Yanru Qu, Hao Zhou, Lei Li, Weinan Zhang, and Yong Yu. 2019 · 2019
Cited alongside, same era.
Simple yet effective bridge reasoning for open-domain multi-hop question answering
Wenhan Xiong, Mo Yu, Xiaoxiao Guo, Hong Wang, Shiyu Chang, Murray Campbell, and William Yang Wang. 2019 · 2019
Cited alongside, same era.
Learning to retrieve reasoning paths over wikipedia graph for question answering
Akari Asai, Kazuma Hashimoto, Hannaneh Hajishirzi, Richard Socher, and Caiming Xiong. 2020 · 2020
Cited alongside, same era.
Electra: Pre-training text encoders as discriminators rather than generators
Kevin Clark, Minh-Thang Luong, Quoc V. Le, and Christopher D. Manning. 2020 · 2020
Cited alongside, same era.
IIRC: A dataset of incomplete information reading comprehension questions
James Ferguson, Matt Gardner, Hannaneh Hajishirzi, Tushar Khot, and Pradeep Dasigi. 2020 · 2020
Cited alongside, same era.
Covidex: Neural ranking models and keyword search infrastructure for the COVID-19 open research dataset
Edwin Zhang, Nikhil Gupta, Raphael Tang, Xiao Han, Ronak Pradeep, Kuang Lu, Yue Zhang, Rodrigo Nogueira, Kyunghyun Cho, Hui Fang, and Jimmy Lin. 2020 · 2020
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Transformer-xh: Multi-evidence reasoning with extra hop attention
Chen Zhao, Chenyan Xiong, Corby Rosset, Xia Song, Paul Bennett, and Saurabh Tiwary. 2020 · 2020
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Summarize-then-answer: Generating concise explanations for multi-hop reading comprehension
Naoya Inoue, Harsh Trivedi, Steven Sinha, Niranjan Balasubramanian, and Kentaro Inui. 2021 · 2021
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Leveraging passage retrieval with generative models for open domain question answering
Gautier Izacard and Edouard Grave. 2021 · 2021
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Dense hierarchical retrieval for open-domain question answering
Ye Liu, Kazuma Hashimoto, Yingbo Zhou, Semih Yavuz, Caiming Xiong, and Philip Yu. 2021 · 2021
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Soloist: Building task bots at scale with transfer learning and machine teaching
Baolin Peng, Chunyuan Li, Jinchao Li, Shahin Shayandeh, Lars Liden, and Jianfeng Gao. 2021 · 2021
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Peng Qi, Haejun Lee, Oghenetegiri "TG" Sido, and Christopher D. Manning. 2021 · 2021
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Memory augmented sequential paragraph retrieval for multi-hop question answering
Nan Shao, Yiming Cui, Ting Liu, Shijin Wang, and Guoping Hu. 2021 · 2021
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Answering complex open-domain questions with multi-hop dense retrieval
Wenhan Xiong, Xiang Li, Srini Iyer, Jingfei Du, Patrick Lewis, William Yang Wang, Yashar Mehdad, Scott Yih, Sebastian Riedel, Douwe Kiela, and Barlas Oguz. 2021 · 2021
Later among the works it cites.