mlsanityData to 14 Oct 2026

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

arXiv 2205.11966 ↗First posted 24 May 2022cs.CLcited by 4

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Abstract (arXiv)

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.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 12 of its 27 references that are in the map. First posted on arXiv 24 May 2022.

Builds on

12 of 27 references.

References · 12

  1. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  2. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  3. 2019An Evaluation Dataset for Intent Classification and Out-of-Scope Predictioncited by 386
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  6. 2020From Arguments to Key Points: Towards Automatic Argument Summarizationcited by 61
  7. 2020Quantitative Argument Summarization and Beyond: Cross-Domain Key Point Analysiscited by 32
  8. 2020HINT3: Raising the bar for Intent Detection in the Wildcited by 21
  9. 2021Every Bite Is an Experience: Key Point Analysis of Business Reviewscited by 19
  10. 2020Expressive Interviewing: A Conversational System for Coping with COVID-19cited by 10
  11. 2021Project Debater APIs: Decomposing the AI Grand Challengecited by 8
  12. 2022Gaining Insights into Unrecognized User Utterances in Task-Oriented Dialog Systemscited by 6

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 2; 2023: 0; 2024: 1; 2025: 0; 2026: 1.

4 papers.