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Related Questions
- What techniques can be used to quantify author bias in machine learning models for entity recognition?
- How can data preprocessing techniques, such as data augmentation and text normalization, help mitigate author bias?
- What role can human annotators play in identifying and correcting biased labels in the training data?
- Can you explain how to use techniques like de-biasing word embeddings and regularization to reduce bias in entity recognition models?
- How can evaluating model performance on diverse test datasets help detect and mitigate author bias?
- What are some effective strategies for handling out-of-vocabulary words and proper nouns in entity recognition to reduce bias?
- Can you discuss how to use techniques like oversampling the minority class and undersampling the majority class to mitigate author bias?
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