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Truth Inference at Scale: A Bayesian Model for Adjudicating Highly
  Redundant Crowd Annotations

Truth Inference at Scale: A Bayesian Model for Adjudicating Highly Redundant Crowd Annotations

24 February 2019
Yuan Li
Benjamin I. P. Rubinstein
Trevor Cohn
ArXivPDFHTML

Papers citing "Truth Inference at Scale: A Bayesian Model for Adjudicating Highly Redundant Crowd Annotations"

5 / 5 papers shown
Title
The Majority Vote Paradigm Shift: When Popular Meets Optimal
The Majority Vote Paradigm Shift: When Popular Meets Optimal
Antonio Purificato
Maria Sofia Bucarelli
Anil Kumar Nelakanti
Andrea Bacciu
Fabrizio Silvestri
Amin Mantrach
68
0
0
18 Feb 2025
Mitigating Observation Biases in Crowdsourced Label Aggregation
Mitigating Observation Biases in Crowdsourced Label Aggregation
Ryosuke Ueda
Koh Takeuchi
H. Kashima
13
2
0
25 Feb 2023
A Light-weight, Effective and Efficient Model for Label Aggregation in
  Crowdsourcing
A Light-weight, Effective and Efficient Model for Label Aggregation in Crowdsourcing
Yi Yang
Zhong-Qiu Zhao
Quan-wei Bai
Qing Liu
Weihua Li
FedML
17
2
0
19 Nov 2022
An Unsupervised Bayesian Neural Network for Truth Discovery in Social
  Networks
An Unsupervised Bayesian Neural Network for Truth Discovery in Social Networks
Jielong Yang
Wee Peng Tay
BDL
21
8
0
25 Jun 2019
Dynamic Bayesian Combination of Multiple Imperfect Classifiers
Dynamic Bayesian Combination of Multiple Imperfect Classifiers
Edwin Simpson
Stephen J. Roberts
Ioannis Psorakis
Arfon M. Smith
58
144
0
08 Jun 2012
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