DS1 spectrogram: Benchmark Data and Evaluation Framework for Intent Discovery Around
  COVID-19 Vaccine Hesitancy

Benchmark Data and Evaluation Framework for Intent Discovery Around COVID-19 Vaccine Hesitancy

May 24, 20222205.11966

Authors

Assaf Toledo,Naor Bar-Zeev,Pooja Sangha,Noam Slonim,Shai Gretz

Abstract

The COVID-19 pandemic has made a huge global impact and cost millions of lives. As COVID-19 vaccines were rolled out, they were quickly met with widespread hesitancy.

To address the concerns of hesitant people, we launched VIRA, a public dialogue system aimed at addressing questions and concerns surrounding the COVID-19 vaccines. Here, we release VIRADialogs, a dataset of over 8k dialogues conducted by actual users with VIRA, providing a unique real-world conversational dataset.

In light of rapid changes in users' intents, due to updates in guidelines or in response to new information, we highlight the important task of intent discovery in this use-case. We introduce a novel automatic evaluation framework for intent discovery, leveraging the existing intent classifier of VIRA.

We use this framework to report baseline intent discovery results over VIRADialogs, that highlight the difficulty of this task.

Resources

Stay in the loop

Get tldr.takara.ai to Your Email, Everyday.

tldr.takara.aiHome·Daily at 6am UTC·© 2026 takara.ai Ltd

Content is sourced from third-party publications.