@inproceedings{lee-sedoc-2020-using,
title = "Using the Poly-encoder for a {COVID}-19 Question Answering System",
author = "Lee, Seolhwa and
Sedoc, Jo{\~a}o",
booktitle = "Proceedings of the 1st Workshop on {NLP} for {COVID}-19 (Part 2) at {EMNLP} 2020",
month = dec,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.nlpcovid19-2.33",
doi = "10.18653/v1/2020.nlpcovid19-2.33",
abstract = "To combat misinformation regarding COVID- 19 during this unprecedented pandemic, we propose a conversational agent that answers questions related to COVID-19. We adapt the Poly-encoder (Humeau et al., 2020) model for informational retrieval from FAQs. We show that after fine-tuning, the Poly-encoder can achieve a higher F1 score. We make our code publicly available for other researchers to use.",
}
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<abstract>To combat misinformation regarding COVID- 19 during this unprecedented pandemic, we propose a conversational agent that answers questions related to COVID-19. We adapt the Poly-encoder (Humeau et al., 2020) model for informational retrieval from FAQs. We show that after fine-tuning, the Poly-encoder can achieve a higher F1 score. We make our code publicly available for other researchers to use.</abstract>
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%0 Conference Proceedings
%T Using the Poly-encoder for a COVID-19 Question Answering System
%A Lee, Seolhwa
%A Sedoc, João
%S Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020
%D 2020
%8 dec
%I Association for Computational Linguistics
%C Online
%F lee-sedoc-2020-using
%X To combat misinformation regarding COVID- 19 during this unprecedented pandemic, we propose a conversational agent that answers questions related to COVID-19. We adapt the Poly-encoder (Humeau et al., 2020) model for informational retrieval from FAQs. We show that after fine-tuning, the Poly-encoder can achieve a higher F1 score. We make our code publicly available for other researchers to use.
%R 10.18653/v1/2020.nlpcovid19-2.33
%U https://aclanthology.org/2020.nlpcovid19-2.33
%U https://doi.org/10.18653/v1/2020.nlpcovid19-2.33
Markdown (Informal)
[Using the Poly-encoder for a COVID-19 Question Answering System](https://aclanthology.org/2020.nlpcovid19-2.33) (Lee & Sedoc, NLP-COVID19 2020)
ACL