Sewon Min

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University of Washington

NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned

We review the EfficientQA competition from NeurIPS 2020. The competition...
01/01/2021 ∙ by Sewon Min, et al. ∙ 15 ∙ share

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

State-of-the-art Machine Reading Comprehension (MRC) models for Open-dom...
10/21/2020 ∙ by Srinivasan Iyer, et al. ∙ 0 ∙ share

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

We present ELQ, a fast end-to-end entity linking model for questions, wh...
10/06/2020 ∙ by Belinda Z. Li, et al. ∙ 0 ∙ share

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AmbigQA: Answering Ambiguous Open-domain Questions

Ambiguity is inherent to open-domain question answering; especially when...
04/22/2020 ∙ by Sewon Min, et al. ∙ 7 ∙ share

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Dense Passage Retrieval for Open-Domain Question Answering

Open-domain question answering relies on efficient passage retrieval to ...
04/10/2020 ∙ by Vladimir Karpukhin, et al. ∙ 0 ∙ share

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Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering

This paper presents a general approach for open-domain question answerin...
11/10/2019 ∙ by Sewon Min, et al. ∙ 30 ∙ share

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Question Answering is a Format; When is it Useful?

Recent years have seen a dramatic expansion of tasks and datasets posed ...
09/25/2019 ∙ by Matt Gardner, et al. ∙ 0 ∙ share

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A Discrete Hard EM Approach for Weakly Supervised Question Answering

Many question answering (QA) tasks only provide weak supervision for how...
09/11/2019 ∙ by Sewon Min, et al. ∙ 0 ∙ share

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Multi-hop Reading Comprehension through Question Decomposition and Rescoring

Multi-hop Reading Comprehension (RC) requires reasoning and aggregation ...
06/07/2019 ∙ by Sewon Min, et al. ∙ 2 ∙ share

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Compositional Questions Do Not Necessitate Multi-hop Reasoning

Multi-hop reading comprehension (RC) questions are challenging because t...
06/07/2019 ∙ by Sewon Min, et al. ∙ 6 ∙ share

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Efficient and Robust Question Answering from Minimal Context over Documents

Neural models for question answering (QA) over documents have achieved s...
05/21/2018 ∙ by Sewon Min, et al. ∙ 0 ∙ share

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Neural Speed Reading via Skim-RNN

Inspired by the principles of speed reading, we introduce Skim-RNN, a re...
11/06/2017 ∙ by Minjoon Seo, et al. ∙ 0 ∙ share

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Question Answering through Transfer Learning from Large Fine-grained Supervision Data

We show that the task of question answering (QA) can significantly benef...
02/07/2017 ∙ by Sewon Min, et al. ∙ 0 ∙ share

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Query-Reduction Networks for Question Answering

In this paper, we study the problem of question answering when reasoning...
06/14/2016 ∙ by Minjoon Seo, et al. ∙ 0 ∙ share

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Sewon Min

Featured Co-authors

Jianfeng Gao

Caiming Xiong

Richard Socher

Luke Zettlemoyer

Sebastian Riedel

Ali Farhadi

Hannaneh Hajishirzi

Jonathan Berant

Xiaodong Liu

Sameer Singh

Edouard Grave

NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned

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

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

AmbigQA: Answering Ambiguous Open-domain Questions

Dense Passage Retrieval for Open-Domain Question Answering

Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering

Question Answering is a Format; When is it Useful?

A Discrete Hard EM Approach for Weakly Supervised Question Answering

Multi-hop Reading Comprehension through Question Decomposition and Rescoring

Compositional Questions Do Not Necessitate Multi-hop Reasoning

Efficient and Robust Question Answering from Minimal Context over Documents

Neural Speed Reading via Skim-RNN

Question Answering through Transfer Learning from Large Fine-grained Supervision Data

Query-Reduction Networks for Question Answering