mlsanityData to 7 Oct 2026

COUGH: A Challenge Dataset and Models for COVID-19 FAQ Retrieval

arXiv 2010.12800 ↗First posted 24 Oct 2020cs.CL cs.IRcited by 10

Not on the map. Why?

Abstract (arXiv)

We present a large, challenging dataset, COUGH, for COVID-19 FAQ retrieval. Similar to a standard FAQ dataset, COUGH consists of three parts: FAQ Bank, Query Bank and Relevance Set. The FAQ Bank contains ~16K FAQ items scraped from 55 credible websites (e.g., CDC and WHO). For evaluation, we introduce Query Bank and Relevance Set, where the former contains 1,236 human-paraphrased queries while the latter contains ~32 human-annotated FAQ items for each query. We analyze COUGH by testing different FAQ retrieval models built on top of BM25 and BERT, among which the best model achieves 48.8 under P@5, indicating a great challenge presented by COUGH and encouraging future research for further improvement. Our COUGH dataset is available at https://github.com/sunlab-osu/covid-faq.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Oct 2020.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 2; 2023: 3; 2024: 1; 2025: 1; 2026: 1.

10 papers.