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Related Questions
- What are the common sources of bias in language data, and how can they impact model performance?
- How do data curation techniques, such as data filtering and augmentation, affect the representation of underrepresented groups in language models?
- Can you explain the concept of 'selection bias' in language data and how it can perpetuate existing social biases?
- What role do human evaluators play in perpetuating biases in language models, and how can their biases be mitigated?
- How do language models' ability to learn from biased data affect their performance on tasks such as sentiment analysis and text classification?
- What are some strategies for addressing bias in language data, such as data preprocessing and debiasing techniques?
- Can you discuss the relationship between data quality and the perpetuation of biases in language models, and how improving data quality can help mitigate these biases?
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