Using the Poly-encoder for a COVID-19 Question Answering System

EMNLP (NLP-COVID19) 2020  ·  Seolhwa Lee, João Sedoc ·

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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