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20192021
most citedLarge-Scale Answerer in Questioner's Mind for Visual Dialog Question Generation

7 citations · 13 across the 3 of their papers we have counts for

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5 papers · 1 filter

cs.CL2021

Designing a Minimal Retrieve-and-Read System for Open-Domain Question Answering

Sohee Yang, Minjoon Seo

In open-domain question answering (QA), retrieve-and-read mechanism has the inherent benefit of interpretability and the easiness of adding, removing, or editing knowledge compared…

cs.CL2021

NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned

Sewon Min, Jordan Boyd-Graber, Chris Alberti +50

We review the EfficientQA competition from NeurIPS 2020. The competition focused on open-domain question answering (QA), where systems take natural language questions as input and…

cs.CL2020

Is Retriever Merely an Approximator of Reader?

Sohee Yang, Minjoon Seo

The state of the art in open-domain question answering (QA) relies on an efficient retriever that drastically reduces the search space for the expensive reader. A rather overlooked…

cs.CL2019

Efficient Dialogue State Tracking by Selectively Overwriting Memory

Sungdong Kim, Sohee Yang, Gyuwan Kim +1

Recent works in dialogue state tracking (DST) focus on an open vocabulary-based setting to resolve scalability and generalization issues of the predefined ontology-based approaches…

cs.CL20197 cited

Large-Scale Answerer in Questioner's Mind for Visual Dialog Question Generation

Sang-Woo Lee, Tong Gao, Sohee Yang +2

Answerer in Questioner's Mind (AQM) is an information-theoretic framework that has been recently proposed for task-oriented dialog systems. AQM benefits from asking a question that…