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Related Questions
- What are some common sources of bias in NLP models and how can they be identified?
- How can contextual understanding be integrated into NLP models to reduce bias and improve performance?
- What techniques can be used to evaluate the fairness and robustness of NLP models in different contexts?
- Can you explain the concept of contextualized embeddings and how they can help mitigate bias in NLP models?
- How can context-aware pre-training be used to improve the performance of NLP models on tasks with diverse linguistic and cultural backgrounds?
- What role does transfer learning play in mitigating bias in NLP models, and how can it be applied in practice?
- Can you discuss the importance of data curation and preprocessing in reducing bias in NLP models, and provide some strategies for doing so?
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