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Learning and Strongly Truthful Multi-Task Peer Prediction: A Variational
  Approach

Learning and Strongly Truthful Multi-Task Peer Prediction: A Variational Approach

30 September 2020
Grant Schoenebeck
Fang-Yi Yu
ArXiv (abs)PDFHTML

Papers citing "Learning and Strongly Truthful Multi-Task Peer Prediction: A Variational Approach"

5 / 5 papers shown
Title
Evaluating LLM-corrupted Crowdsourcing Data Without Ground Truth
Evaluating LLM-corrupted Crowdsourcing Data Without Ground Truth
Yichi Zhang
Jinlong Pang
Zhaowei Zhu
Yang Liu
13
1
0
08 Jun 2025
Stochastically Dominant Peer Prediction
Stochastically Dominant Peer Prediction
Yichi Zhang
Shengwei Xu
David Pennock
Grant Schoenebeck
18
0
0
02 Jun 2025
Eliciting Informative Text Evaluations with Large Language Models
Eliciting Informative Text Evaluations with Large Language Models
Yuxuan Lu
Shengwei Xu
Yichi Zhang
Yuqing Kong
Grant Schoenebeck
65
7
0
23 May 2024
Spot Check Equivalence: an Interpretable Metric for Information
  Elicitation Mechanisms
Spot Check Equivalence: an Interpretable Metric for Information Elicitation Mechanisms
Shengwei Xu
Yichi Zhang
Paul Resnick
Grant Schoenebeck
41
4
0
21 Feb 2024
The Square Root Agreement Rule for Incentivizing Truthful Feedback on
  Online Platforms
The Square Root Agreement Rule for Incentivizing Truthful Feedback on Online Platforms
Vijay Kamble
Nihar B. Shah
David Marn
Abhay K. Parekh
Kannan Ramchandran
30
5
0
25 Jul 2015
1