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Related Questions
- What are some strategies for human annotators to ensure consistency in labeling data?
- How can annotators minimize their own biases when labeling data for machine learning models?
- What are some best practices for annotators to follow when working with sensitive or ambiguous data?
- Can annotators use active learning techniques to reduce the need for human judgment?
- How can annotators verify the quality of their annotations to ensure they are accurate and unbiased?
- What are some techniques for annotators to detect and mitigate annotation drift over time?
- Can annotators use multiple annotators to validate and compare their annotations to reduce bias?
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