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NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned
[article]
2021
arXiv
pre-print
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We review the EfficientQA competition from NeurIPS 2020. ...
In this report, we describe the motivation and organization of the competition, review the best submissions, and analyze system predictions to inform a discussion of evaluation for open-domain QA. ...
Acknowledgments We thank all the participants for taking part and making this a successful competition. We thank Google for providing prizes for computer participants. ...
arXiv:2101.00133v2
fatcat:i3pwpxnarzeghoo7ggjlqk57xm
Designing a Minimal Retrieve-and-Read System for Open-Domain Question Answering
[article]
2021
arXiv
pre-print
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A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
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Here, we discuss several orthogonal strategies to drastically reduce the footprint of a retrieve-and-read open-domain QA system by up to 160x. ...
model with comparable docker-level system size. ...
Weld, and Luke competition: Systems, analyses and lessons learned.
Zettlemoyer. 2017. Triviaqa: A large scale distantly arXiv preprint arXiv:2101.00133. ...
arXiv:2104.07242v2
fatcat:enlrajzwhnhszp5juwvbxzre2i
Boosting Search Engines with Interactive Agents
[article]
2021
arXiv
pre-print
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A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:
2021 pre-print arXiv:2109.00527v1 fatcat:ox2upf3v25gchalklym5j2yg2u
Agents are then empowered with simple but effective search operators to exert fine-grained and transparent control over queries and search results. ...
We also present a reinforcement learning agent with dynamically constrained actions that learns interactive search strategies from scratch. ...
Mehdad, and
W. tau Yih. NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned,
2021.
V. Mnih, K. Kavukcuoglu, D. Silver, A. Graves, I. Antonoglou, D. Wierstra, and M. ...
arXiv:2109.00527v2
fatcat:kbgdfibgg5fgriyagc7ae7wo6i