Tripartite Intelligence: Synergizing Deep Neural Network, Large Language Model, and Human Intelligence for Public Health Misinformation Detection (Archival Full Paper)-Reference-Cited by-同舟云学术

Tripartite Intelligence: Synergizing Deep Neural Network, Large Language Model, and Human Intelligence for Public Health Misinformation Detection (Archival Full Paper)

Published:2024-06-27 Issue: Volume:35 Page:63-75
ISSN:
Container-title:Proceedings of the ACM Collective Intelligence Conference
language:
Short-container-title:

Author:

Zhang Yang¹^ORCID,Zong Ruohan²^ORCID,Shang Lanyu³^ORCID,Yue Zhenrui²^ORCID,Zeng Huimin⁴^ORCID,Liu Yifan¹^ORCID,Wang Dong⁵^ORCID

Affiliation:

1. School of Information Sciences, University of Illinois at Urbana-Champaign, USA

2. School of Information Sciences, University of Illinois Urbana-Champaign, USA

3. School of Information Science, University of Illinois Urbana-Champaign, USA

4. Information Science, University of Illinois at Urbana-Champaign, USA

5. University of Illinois at Urbana-Champaign, USA

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3643562.3672613

Reference63 articles.

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3. Inter-Coder Agreement for Computational Linguistics

4. Canyu Chen and Kai Shu. 2023. Combating misinformation in the age of llms: Opportunities and challenges. arXiv preprint arXiv:2311.05656 (2023).

5. Wei-Yu Chen, Yen-Cheng Liu, Zsolt Kira, Yu-Chiang Frank Wang, and Jia-Bin Huang. 2019. A Closer Look at Few-shot Classification. In International Conference on Learning Representations.