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Related Questions
- Can keyword-based methods for negative example collection inadvertently select examples that reinforce existing biases in the data?
- How do keyword-based methods handle nuances in language that may lead to biased or incomplete negative example selection?
- Can keyword-based methods overlook subtle patterns or relationships in the data that contribute to bias?
- Do keyword-based methods rely too heavily on surface-level features, potentially missing deeper, more complex biases?
- In what ways can keyword-based methods be influenced by the annotators' own biases and assumptions?
- Can keyword-based methods fail to capture context-dependent biases that arise from the specific task or domain?
- How do keyword-based methods handle the issue of 'bias creep,' where biases are introduced or amplified through the collection process?
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