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Related Questions
- What are some common sources of data bias in pre-training data?
- Can you explain the concept of data curation and its role in mitigating bias?
- How do language models perpetuate and amplify existing biases in the data they are trained on?
- What are some techniques for data augmentation that can help reduce bias?
- Can you discuss the importance of diversity and representation in the data used to pre-train language models?
- What is the relationship between data quality and data bias, and how can we prioritize data quality?
- Are there any specific metrics or evaluation methods that can help identify and mitigate bias in pre-trained models?
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