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Incentivizing evaluation with peer prediction and limited access to ground truth

  • Published:2019-10 Issue: Volume:275 Page:618-638
  • ISSN:0004-3702
  • Container-title:Artificial Intelligence
  • language:en
  • Short-container-title:Artificial Intelligence

Author:

Gao Xi Alice,Wright James R.ORCID,Leyton-Brown KevinORCID

Funder

Natural Sciences and Engineering Research Council of Canada

Google

Publisher

Elsevier BV

Subject

Artificial Intelligence,Linguistics and Language,Language and Linguistics

Reference42 articles.

1. Incentives for Truthful Peer Grading;de Alfaro,2015

2. Crowdgrader: a tool for crowdsourcing the evaluation of homework assignments;de Alfaro,2014

3. Aggregating partial rankings with applications to peer grading in massive online open courses;Caragiannis,2015

4. Scaffolded writing and rewriting in the discipline: a web-based reciprocal peer review system;Cho;Comput. Educ.,2007

5. Crowdsourced judgement elicitation with endogenous proficiency;Dasgupta,2013

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2. Spot Check Equivalence: An Interpretable Metric for Information Elicitation Mechanisms;Proceedings of the ACM Web Conference 2024;2024-05-13

3. Mechanical TA 2: Peer Grading with TA and Algorithmic Support;Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1;2024-03-07

4. The Square Root Agreement Rule for Incentivizing Truthful Feedback on Online Platforms;Management Science;2023-01

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