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.- Anthology ID:
- 2020.nlpcovid19-2.33
- Volume:
- Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020
- Month:
- December
- Year:
- 2020
- Address:
- Online
- Venue:
- NLP-COVID19
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- Language:
- URL:
- https://aclanthology.org/2020.nlpcovid19-2.33
- DOI:
- 10.18653/v1/2020.nlpcovid19-2.33
- Cite (ACL):
- Seolhwa Lee and João Sedoc. 2020. Using the Poly-encoder for a COVID-19 Question Answering System. In Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020, Online. Association for Computational Linguistics.
- Cite (Informal):
- Using the Poly-encoder for a COVID-19 Question Answering System (Lee & Sedoc, NLP-COVID19 2020)
- PDF:
- https://preview.aclanthology.org/paclic-22-ingestion/2020.nlpcovid19-2.33.pdf
- Code
- sseol11/Parlai_ver2 + additional community code
- Data
- WikiQA