CollabEquality: A Crowd-AI Collaborative Learning Framework to Address Class-wise Inequality in Web-based Disaster Response-Reference-Cited by-同舟云学术

CollabEquality: A Crowd-AI Collaborative Learning Framework to Address Class-wise Inequality in Web-based Disaster Response

Published:2023-04-30 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the ACM Web Conference 2023
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Author:

Zhang Yang¹^ORCID,Shang Lanyu¹^ORCID,Zong Ruohan¹^ORCID,Zeng Huimin¹^ORCID,Yue Zhenrui¹^ORCID,Wang Dong¹^ORCID

Affiliation:

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

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3543507.3583871

Reference67 articles.

1. CrisisMMD: Multimodal Twitter Datasets from Natural Disasters

2. Crowdsourcing Subjective Tasks: The Case Study of Understanding Toxicity in Online Discussions

3. What do You Mean? Interpreting Image Classification with Crowdsourced Concept Extraction and Analysis

4. Philipp Benz Chaoning Zhang Soomin Ham Adil Karjauv Gyusang Cho and In So Kweon. [n. d.]. Trade-off Between Accuracy Robustness and Fairness of Deep Classifiers. ([n. d.]). Philipp Benz Chaoning Zhang Soomin Ham Adil Karjauv Gyusang Cho and In So Kweon. [n. d.]. Trade-off Between Accuracy Robustness and Fairness of Deep Classifiers. ([n. d.]).

5. A deep learning-based social media text analysis framework for disaster resource management

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