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Sewon Min

Noisy Channel Language Model Prompting for Few-Shot Text Classification


Aug 15, 2021
Sewon Min, Mike Lewis, Hannaneh Hajishirzi, Luke Zettlemoyer

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* 15 pages, 6 figures 
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FaVIQ: FAct Verification from Information-seeking Questions


Jul 05, 2021
Jungsoo Park, Sewon Min, Jaewoo Kang, Luke Zettlemoyer, Hannaneh Hajishirzi

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* 12 pages, 3 figures; Data & Code available at https://faviq.github.io 
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Joint Passage Ranking for Diverse Multi-Answer Retrieval


Apr 17, 2021
Sewon Min, Kenton Lee, Ming-Wei Chang, Kristina Toutanova, Hannaneh Hajishirzi

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* 13 pages 
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NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned


Jan 01, 2021
Sewon Min, Jordan Boyd-Graber, Chris Alberti, Danqi Chen, Eunsol Choi, Michael Collins, Kelvin Guu, Hannaneh Hajishirzi, Kenton Lee, Jennimaria Palomaki, Colin Raffel, Adam Roberts, Tom Kwiatkowski, Patrick Lewis, Yuxiang Wu, Heinrich Küttler, Linqing Liu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel, Sohee Yang, Minjoon Seo, Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Edouard Grave, Ikuya Yamada, Sonse Shimaoka, Masatoshi Suzuki, Shumpei Miyawaki, Shun Sato, Ryo Takahashi, Jun Suzuki, Martin Fajcik, Martin Docekal, Karel Ondrej, Pavel Smrz, Hao Cheng, Yelong Shen, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Barlas Oguz, Xilun Chen, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Schlichtkrull, Sonal Gupta, Yashar Mehdad, Wen-tau Yih

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* 26 pages 
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RECONSIDER: Re-Ranking using Span-Focused Cross-Attention for Open Domain Question Answering


Oct 21, 2020
Srinivasan Iyer, Sewon Min, Yashar Mehdad, Wen-tau Yih

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Efficient One-Pass End-to-End Entity Linking for Questions


Oct 06, 2020
Belinda Z. Li, Sewon Min, Srinivasan Iyer, Yashar Mehdad, Wen-tau Yih

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* 9 pages, EMNLP 2020 
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Dense Passage Retrieval for Open-Domain Question Answering


May 02, 2020
Vladimir Karpukhin, Barlas OÄŸuz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, Wen-tau Yih

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* corrected typos in Table 3; add a paragraph in Sec. 6.2 
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AmbigQA: Answering Ambiguous Open-domain Questions


Apr 22, 2020
Sewon Min, Julian Michael, Hannaneh Hajishirzi, Luke Zettlemoyer

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Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering


Nov 10, 2019
Sewon Min, Danqi Chen, Luke Zettlemoyer, Hannaneh Hajishirzi

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Question Answering is a Format; When is it Useful?


Sep 25, 2019
Matt Gardner, Jonathan Berant, Hannaneh Hajishirzi, Alon Talmor, Sewon Min


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A Discrete Hard EM Approach for Weakly Supervised Question Answering


Sep 11, 2019
Sewon Min, Danqi Chen, Hannaneh Hajishirzi, Luke Zettlemoyer

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* Published as a conference paper at EMNLP 2019 (long). Code available at https://github.com/shmsw25/qa-hard-em 
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Multi-hop Reading Comprehension through Question Decomposition and Rescoring


Jun 30, 2019
Sewon Min, Victor Zhong, Luke Zettlemoyer, Hannaneh Hajishirzi

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* Published as a conference paper at ACL 2019 (long). Code available at https://github.com/shmsw25/DecompRC 
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Compositional Questions Do Not Necessitate Multi-hop Reasoning


Jun 07, 2019
Sewon Min, Eric Wallace, Sameer Singh, Matt Gardner, Hannaneh Hajishirzi, Luke Zettlemoyer

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* Published as a conference paper at ACL 2019 (short). Code available at https://github.com/shmsw25/single-hop-rc 
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Question Answering through Transfer Learning from Large Fine-grained Supervision Data


Jun 21, 2018
Sewon Min, Minjoon Seo, Hannaneh Hajishirzi

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* Published as a conference paper at ACL 2017 (short paper). Code available at https://github.com/shmsw25/qa-transfer 
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Efficient and Robust Question Answering from Minimal Context over Documents


May 21, 2018
Sewon Min, Victor Zhong, Richard Socher, Caiming Xiong

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* Published as a conference paper at ACL 2018 (long paper) 
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Neural Speed Reading via Skim-RNN


Mar 29, 2018
Minjoon Seo, Sewon Min, Ali Farhadi, Hannaneh Hajishirzi

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* ICLR 2018 
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Query-Reduction Networks for Question Answering


Feb 24, 2017
Minjoon Seo, Sewon Min, Ali Farhadi, Hannaneh Hajishirzi

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* Published as a conference paper at ICLR 2017. Title of the paper has changed from "Query-Regression Networks for Machine Comprehension" 
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