Papers by Bryan Eaton
A Mixed-Method Design Approach for Empirically Based Selection of Unbiased Data Annotators (2021.findings-acl)
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| Challenge: | Current approaches to selecting annotators are limited at the policy-guidance level, rendering them unusable for machine learning practitioners. |
| Approach: | They propose a method that is functional, adaptable, and simpler to implement in selecting unbiased annotators for any machine learning problem. |
| Outcome: | The proposed approach is functional, adaptable, and simpler to implement on a real-world geopolitical problem. |