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20202024
most citedModeling and mitigating human annotation errors to design efficient stream processing systems with human-in-the-loop machine learning

44 citations · 49 across the 6 of their papers we have counts for

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cs.HC2024

Closing the Knowledge Gap in Designing Data Annotation Interfaces for AI-powered Disaster Management Analytic Systems

Zinat Ara, Hossein Salemi, Sungsoo Ray Hong +4

Data annotation interfaces predominantly leverage ground truth labels to guide annotators toward accurate responses. With the growing adoption of Artificial Intelligence (AI) in do…

cs.HC2020★ 44 cited

Modeling and mitigating human annotation errors to design efficient stream processing systems with human-in-the-loop machine learning

Rahul Pandey, Hemant Purohit, Carlos Castillo +1

High-quality human annotations are necessary for creating effective machine learning-driven stream processing systems. We study hybrid stream processing systems based on a Human-In…