18 citations · 94 across the 21 of their papers we have counts for
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cs.HC2023
Recovering Top-Two Answers and Confusion Probability in Multi-Choice Crowdsourcing
Hyeonsu Jeong, Hye Won Chung
Crowdsourcing has emerged as an effective platform for labeling large amounts of data in a cost- and time-efficient manner. Most previous work has focused on designing an efficient…
cs.HC2021★ 1 cited
A Worker-Task Specialization Model for Crowdsourcing: Efficient Inference and Fundamental Limits
Doyeon Kim, Jeonghwan Lee, Hye Won Chung
Crowdsourcing system has emerged as an effective platform for labeling data with relatively low cost by using non-expert workers. Inferring correct labels from multiple noisy answe…
cs.HC2020
Crowdsourced Labeling for Worker-Task Specialization Model
Doyeon Kim, Hye Won Chung
We consider crowdsourced labeling under a -type worker-task specialization model, where each worker and task is associated with one particular type among a finite set of types a…