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Related Questions
- What role does data diversity play in ensuring the fairness and accuracy of pre-trained language models?
- How can biased data affect the performance of pre-trained language models in real-world applications?
- Can you explain the concept of data curation in the context of machine learning and language models?
- What strategies can be employed to detect and mitigate biases in pre-trained language models?
- How does the quality of training data impact the robustness of pre-trained language models to out-of-distribution inputs?
- What are some best practices for curating high-quality training data for pre-trained language models?
- Can you discuss the relationship between data curation and the generalizability of pre-trained language models across different domains and tasks?
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