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Related Questions
- Can annotator biases affect the quality of the training data for machine learning models?
- How do annotators' cultural backgrounds influence their interpretation of context and semantics in text?
- What are the potential consequences of relying on a single annotator's perspective for model development?
- Can annotator experiences with similar tasks impact their understanding and annotation of new tasks?
- How can the annotation process be designed to minimize the impact of annotator perspectives on model performance?
- What strategies can be employed to ensure that annotators' perspectives are diverse and representative of the target population?
- Can the use of multiple annotators with different perspectives improve the robustness and accuracy of the model?
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